From a436d67cbc722035964f75ff350792d0a3606789 Mon Sep 17 00:00:00 2001
From: Charles Fettinger <charles@onacloud.org>
Date: Mon, 6 Apr 2026 11:21:58 -0700
Subject: [PATCH 1/6] Add multi-LLM support and update dependencies in README
 and agent.py

---
 README.md      | 54 ++++++++++++++++++++++++++++++++++++++++++++++++++
 agent.py       | 30 +++++++++++++++++++++++++---
 pyproject.toml |  1 +
 3 files changed, 82 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 1d7fcd11..924d373e 100644
--- a/README.md
+++ b/README.md
@@ -66,6 +66,60 @@ rm -rf jobs; mkdir -p jobs && uv run harbor run -p tasks/ --task-name "<task-nam
 rm -rf jobs; mkdir -p jobs && uv run harbor run -p tasks/ -n 100 --agent-import-path agent:AutoAgent -o jobs --job-name latest > run.log 2>&1
 ```
 
+## Multi-LLM Support
+
+The harness supports multiple LLM providers via [LiteLLM](https://github.com/BerriAI/litellm). Configure via environment variables:
+
+### Environment Variables
+
+- `LLM_PROVIDER`: Provider name (`openai`, `anthropic`, `ollama`, `azure`, etc.)
+- `MODEL`: Model name (e.g., `gpt-5`, `claude-3-5-sonnet`, `qwen3.5:35b-a3b-q8_0`)
+- `LLM_BASE_URL`: Optional base URL (required for Ollama, Azure, etc.)
+- `API_KEY`: Provider-specific API key (e.g., `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`)
+
+### Using Local Ollama
+
+```bash
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.5:35b-a3b-q8_0
+LLM_BASE_URL=http://host.docker.internal:11434/v1
+EOF
+```
+
+### Using OpenAI
+
+```bash
+cat > .env << 'EOF'
+LLM_PROVIDER=openai
+MODEL=gpt-5
+OPENAI_API_KEY=your-api-key
+EOF
+```
+
+### Using Anthropic
+
+```bash
+cat > .env << 'EOF'
+LLM_PROVIDER=anthropic
+MODEL=claude-3-5-sonnet
+ANTHROPIC_API_KEY=your-api-key
+EOF
+```
+
+### Using Azure
+
+```bash
+cat > .env << 'EOF'
+LLM_PROVIDER=azure
+MODEL=your-deployment-name
+AZURE_API_KEY=your-api-key
+AZURE_API_BASE=https://your-resource.openai.azure.com
+EOF
+```
+
+The model selection is optional and can be changed dynamically by modifying the environment variables before running the benchmark.
+
 ## Running the meta-agent
 
 Point your coding agent at the repo and prompt:
diff --git a/agent.py b/agent.py
index d155db41..b104b6bd 100644
--- a/agent.py
+++ b/agent.py
@@ -26,8 +26,18 @@
 # ============================================================================
 
 SYSTEM_PROMPT = "You are an agent that executes tasks"
-MODEL = "gpt-5"
-MAX_TURNS = 30
+MAX_TURNS = 15
+
+# Multi-LLM configuration via LiteLLM
+# Set environment variables before running:
+# - LLM_PROVIDER: "openai", "anthropic", "ollama", "azure", etc.
+# - MODEL: model name (e.g., "gpt-5", "claude-3-5-sonnet", "qwen3.5:35b-a3b-q8_0")
+# - LLM_BASE_URL: optional base URL (required for Ollama, Azure, etc.)
+# - API_KEY: provider-specific API key (e.g., OPENAI_API_KEY, ANTHROPIC_API_KEY)
+import os
+LLM_PROVIDER = os.getenv("LLM_PROVIDER", "openai").lower()
+MODEL = os.getenv("MODEL", "gpt-5")
+LLM_BASE_URL = os.getenv("LLM_BASE_URL")
 
 
 def create_tools(environment: BaseEnvironment) -> list[FunctionTool]:
@@ -53,11 +63,25 @@ async def run_shell(command: str) -> str:
 def create_agent(environment: BaseEnvironment) -> Agent:
     """Build the agent. Modify to add handoffs, sub-agents, or agent-as-tool."""
     tools = create_tools(environment)
+    
+    # Build LiteLLM-compatible model string
+    if LLM_PROVIDER == "ollama":
+        # Ollama uses custom base URL format
+        model_string = f"ollama_chat/{MODEL}" if not LLM_BASE_URL else f"ollama_chat/{MODEL}"
+    elif LLM_PROVIDER == "azure":
+        # Azure uses deployment name format
+        model_string = f"azure/{MODEL}"
+    elif LLM_PROVIDER == "anthropic":
+        model_string = f"anthropic/{MODEL}"
+    else:
+        # Default to OpenAI format
+        model_string = MODEL
+    
     return Agent(
         name="autoagent",
         instructions=SYSTEM_PROMPT,
         tools=tools,
-        model=MODEL,
+        model=model_string,
     )
 
 
diff --git a/pyproject.toml b/pyproject.toml
index c419b630..df8ceb72 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,4 +9,5 @@ dependencies = [
     "openpyxl",
     "numpy",
     "harbor",
+    "litellm>=1.60.0",
 ]

From 68460c1124bb66b01aaad7878b0edbcefb41f977 Mon Sep 17 00:00:00 2001
From: Charles Fettinger <Charles@onacloud.org>
Date: Wed, 26 Aug 2026 10:53:22 -0700
Subject: [PATCH 2/6] Add logo

---
 .gitignore    |   3 ++-
 README.md     |   5 +----
 docs/logo.png | Bin 0 -> 256224 bytes
 3 files changed, 3 insertions(+), 5 deletions(-)
 create mode 100644 docs/logo.png

diff --git a/.gitignore b/.gitignore
index c89e06d3..c4fe8f5d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -20,4 +20,5 @@ tasks-archived-sheets/
 tasks-sheets-verified/
 tasks-sheets/
 
-dev/
\ No newline at end of file
+dev/
+/.vs
diff --git a/README.md b/README.md
index 924d373e..b98b3097 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,5 @@
 <p align="center">
-  <a href="https://www.thirdlayer.inc">
-    <img src="https://www.thirdlayer.inc/thirdlayer-logo.svg" alt="thirdlayer" width="200">
-  </a>
+  <img src="docs/logo.png" alt="open-autoagent" width="160">
 </p>
 
 <blockquote>
@@ -207,4 +205,3 @@ You can equip the agent with [Agent Skills for Context Engineering](https://gith
 ## License
 
 MIT
-
diff --git a/docs/logo.png b/docs/logo.png
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HcmV?d00001


From 7031031a26318549f146aad246edd83eb9470824 Mon Sep 17 00:00:00 2001
From: Charles Fettinger <Charles@onacloud.org>
Date: Wed, 26 Aug 2026 12:49:54 -0700
Subject: [PATCH 3/6] Add open-autoagent-ollama-setup skill & quick installer

Added a new skill for setting up open-autoagent with a host-native Ollama daemon, targeting Harbor harness experiments on AMD Ryzen AI Max+ 395. Introduced quick installer scripts (Bash/PowerShell) for harness selection and skill deployment. Updated README with install instructions and harness triggers. Comprehensive SKILL.md covers setup steps, preconditions, repo config, environment, patching, Docker build, Harbor scaffolding, baseline run, operator guidance, and forbidden actions. Installer and docs ensure reproducible, harness-agnostic setup for AI-driven experiments. Does not cover torrent MCP server or live download orchestration.

Add cross-platform installer & harness integration for skill

Automates installation of `open-autoagent-ollama-setup` across Linux/macOS (sh) and Windows (PowerShell) with `install.*` and `configure.*` scripts.
Introduces `.skill-config.json` (gitignored) for pre-configuration of repo, LLM, model, endpoint, and hardware profile.
Adds `SKILL.md.template` for dynamic skill doc generation per environment.
Documents setup workflow in `SETUP_WORKFLOW.md` and updates README with quick AI harness install instructions.
No changes to core setup logic or skill instructions; canonical docs now serve as installer defaults.
Adds `.skill-config.json` to `.gitignore`.

Add AI harness installer and setup workflow for skill

Adds interactive setup/install scripts for open-autoagent-ollama-setup skill, supporting quick or custom config for repo/model/hardware. Scripts generate .skill-config.json (gitignored) and install the skill for multiple AI harnesses (Hermes, Claude, Cursor, Grok, VS Code, Visual Studio). Adds SKILL.md.template, .skill-config.json.example, SETUP_WORKFLOW.md, and updates README with install instructions. No core code changes; improves reproducibility and customization of skill installation.
---
 README.md                             |  28 ++
 setup/.gitignore                      |   1 +
 setup/.skill-config.json.example      |  17 +
 setup/SETUP_WORKFLOW.md               |  77 +++++
 setup/SKILL.md.template               | 180 +++++++++++
 setup/configure.ps1                   |  87 +++++
 setup/configure.sh                    |  71 +++++
 setup/harness/claude-code/SKILL.md    | 437 ++++++++++++++++++++++++++
 setup/harness/claude-desktop/SKILL.md | 437 ++++++++++++++++++++++++++
 setup/harness/cursor/SKILL.md         | 437 ++++++++++++++++++++++++++
 setup/harness/grok/SKILL.md           | 437 ++++++++++++++++++++++++++
 setup/harness/hermes/SKILL.md         | 437 ++++++++++++++++++++++++++
 setup/harness/visual-studio/SKILL.md  | 437 ++++++++++++++++++++++++++
 setup/harness/vscode/SKILL.md         | 437 ++++++++++++++++++++++++++
 setup/install.ps1                     | 171 ++++++++++
 setup/install.sh                      | 155 +++++++++
 setup/open-autoagent-ollama-setup.md  | 437 ++++++++++++++++++++++++++
 17 files changed, 4283 insertions(+)
 create mode 100644 setup/.gitignore
 create mode 100644 setup/.skill-config.json.example
 create mode 100644 setup/SETUP_WORKFLOW.md
 create mode 100644 setup/SKILL.md.template
 create mode 100644 setup/configure.ps1
 create mode 100644 setup/configure.sh
 create mode 100644 setup/harness/claude-code/SKILL.md
 create mode 100644 setup/harness/claude-desktop/SKILL.md
 create mode 100644 setup/harness/cursor/SKILL.md
 create mode 100644 setup/harness/grok/SKILL.md
 create mode 100644 setup/harness/hermes/SKILL.md
 create mode 100644 setup/harness/visual-studio/SKILL.md
 create mode 100644 setup/harness/vscode/SKILL.md
 create mode 100644 setup/install.ps1
 create mode 100644 setup/install.sh
 create mode 100644 setup/open-autoagent-ollama-setup.md

diff --git a/README.md b/README.md
index b98b3097..3aface68 100644
--- a/README.md
+++ b/README.md
@@ -64,6 +64,34 @@ rm -rf jobs; mkdir -p jobs && uv run harbor run -p tasks/ --task-name "<task-nam
 rm -rf jobs; mkdir -p jobs && uv run harbor run -p tasks/ -n 100 --agent-import-path agent:AutoAgent -o jobs --job-name latest > run.log 2>&1
 ```
 
+## Install quickly with an AI harness
+
+The `setup/` folder installs a skill that lets your AI harness run the full
+Ollama setup for you — clone, `.env`, `uv sync`, Docker base image, Harbor
+smoke test.
+
+```bash
+# Linux / macOS / Git Bash
+bash setup/install.sh
+
+# Windows PowerShell
+.\setup\install.ps1
+```
+
+Pick your harness when prompted, then trigger it:
+
+| Harness | Trigger |
+|---|---|
+| Hermes | New session (or `/reset`) → `run open-autoagent-ollama-setup` |
+| Claude Code | In chat: `run open-autoagent-ollama-setup` |
+| Claude Desktop | In chat: `run open-autoagent-ollama-setup` |
+| Cursor | In chat: `run open-autoagent-ollama-setup` |
+| Grok | In chat: `run open-autoagent-ollama-setup` |
+| VS Code + Copilot | `Ctrl+Shift+I` → `#file:.vscode/skills/open-autoagent-ollama-setup/SKILL.md` → `run open-autoagent-ollama-setup` |
+| Visual Studio | `View > GitHub Copilot Chat` → `#file:.github/skills/open-autoagent-ollama-setup/SKILL.md` → `run open-autoagent-ollama-setup` |
+
+The harness will execute every step and stop if a check fails.
+
 ## Multi-LLM Support
 
 The harness supports multiple LLM providers via [LiteLLM](https://github.com/BerriAI/litellm). Configure via environment variables:
diff --git a/setup/.gitignore b/setup/.gitignore
new file mode 100644
index 00000000..9607b875
--- /dev/null
+++ b/setup/.gitignore
@@ -0,0 +1 @@
+.skill-config.json
diff --git a/setup/.skill-config.json.example b/setup/.skill-config.json.example
new file mode 100644
index 00000000..994fc447
--- /dev/null
+++ b/setup/.skill-config.json.example
@@ -0,0 +1,17 @@
+{
+  "mainRepo": "https://github.com/Oncorporation/open-autoagent",
+  "domainRepo": "https://github.com/Oncorporation/secure-torrent-mcp-agent",
+  "domainBranch": "domain/secure-torrent",
+  "llmProvider": "ollama",
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "ollamaEndpoint": "http://127.0.0.1:11434",
+  "hardware": "AMD Ryzen AI Max+ 395 64GB-64GB",
+  "skillMetadata": {
+    "name": "open-autoagent-ollama-setup",
+    "description": "Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments.",
+    "license": "MIT",
+    "version": "1.0.0",
+    "hermesTags": ["open-autoagent", "ollama", "harbor", "harness"],
+    "hermesCategory": "mcp-install"
+  }
+}
diff --git a/setup/SETUP_WORKFLOW.md b/setup/SETUP_WORKFLOW.md
new file mode 100644
index 00000000..71cfd073
--- /dev/null
+++ b/setup/SETUP_WORKFLOW.md
@@ -0,0 +1,77 @@
+# Setup Workflow
+
+The setup folder now supports **generic repository setup** via optional configuration.
+
+## Workflow
+
+### Option 1: Quick Start (Default)
+Use the original hardcoded repo, model, and settings:
+
+```bash
+# Linux / macOS
+bash setup/install.sh
+
+# Windows PowerShell
+.\setup\install.ps1
+```
+
+Pick your harness, install, done. Defaults:
+- Repo: `https://github.com/Oncorporation/open-autoagent`
+- Model: `qwen3.8:27b-mtp-q8_0`
+- Ollama: `http://127.0.0.1:11434`
+
+### Option 2: Custom Configuration
+Use your own repo, model, hardware, LLM provider:
+
+```bash
+# 1. Configure
+bash setup/configure.sh          # Linux/macOS
+.\setup\configure.ps1            # Windows
+
+# 2. Install
+bash setup/install.sh            # Linux/macOS
+.\setup\install.ps1              # Windows
+```
+
+The installer checks for `.skill-config.json` and uses it to customize the
+SKILL.md before copying. If no config exists, defaults are used.
+
+## What Gets Configured
+
+| Setting | Purpose | Default |
+|---|---|---|
+| Main repo | GitHub/HF/local path to clone | `https://github.com/Oncorporation/open-autoagent` |
+| Domain repo | Optional catalog/context repo | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | Branch name in main repo | `domain/secure-torrent` |
+| LLM provider | `ollama`, `openai`, `anthropic`, `azure` | `ollama` |
+| Model | Model name/tag | `qwen3.8:27b-mtp-q8_0` |
+| Ollama endpoint | Only if provider=ollama | `http://127.0.0.1:11434` |
+| Hardware | Info string (notes only) | `AMD Ryzen AI Max+ 395 64GB-64GB` |
+
+## How It Works
+
+1. **`configure.sh/.ps1`** → prompts → saves to `.skill-config.json`
+2. **`install.sh/.ps1`** → reads config (or defaults) → processes `SKILL.md.template` → installs customized SKILL.md
+3. **Harness triggers** → runs the skill with custom repo/model/hardware baked in
+
+`.skill-config.json` is gitignored so it never gets committed.
+
+## Adding a New Harness
+
+1. Create `setup/harness/new-harness/` directory
+2. **Either:**
+   - Pre-build: copy `SKILL.md.template` → `new-harness/SKILL.md` (installers will use it as-is)
+   - Or: install will auto-generate from template + config
+3. Update installer menu (both `.sh` and `.ps1`) with harness option and trigger instructions
+4. Done — installers pick up the new folder automatically
+
+## Files
+
+| File | Purpose |
+|---|---|
+| `configure.sh` / `configure.ps1` | Prompt user for custom config → save to `.skill-config.json` |
+| `install.sh` / `install.ps1` | Read config (or defaults) → process template → install to harness |
+| `SKILL.md.template` | Generic skill template with `{{PLACEHOLDERS}}` |
+| `.skill-config.json` | User config (created by configure, gitignored) |
+| `harness/*/SKILL.md` | Pre-built harness-specific skills (optional) |
+| `open-autoagent-ollama-setup.md` | Legacy canonical skill (fallback only) |
diff --git a/setup/SKILL.md.template b/setup/SKILL.md.template
new file mode 100644
index 00000000..7fc08877
--- /dev/null
+++ b/setup/SKILL.md.template
@@ -0,0 +1,180 @@
+#!/usr/bin/env bash
+# SKILL.md.template — Template for open-autoagent-ollama-setup skill
+#
+# This file is processed by install.sh to inject custom repo/model/hardware info.
+# Placeholders: {{MAIN_REPO}}, {{DOMAIN_REPO}}, {{DOMAIN_BRANCH}}, {{MODEL}}, {{OLLAMA_ENDPOINT}}, {{HARDWARE}}
+
+---
+name: open-autoagent-ollama-setup
+description: Set up {{MAIN_REPO}} on {{HARDWARE}}. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor, or work with the domain branch. Do not use for torrent MCP or download-orchestrator only.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: {{HARDWARE}}
+  model: {{MODEL}}
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check.
+
+## Locked settings from the project session
+
+| Key | Value |
+|---|---|
+| Repo | `{{MAIN_REPO}}` |
+| Domain catalog | `{{DOMAIN_REPO}}` |
+| Domain branch | `{{DOMAIN_BRANCH}}` |
+| LLM provider | `ollama` |
+| Model tag | `{{MODEL}}` |
+| Ollama bind | `{{OLLAMA_ENDPOINT}}` |
+| Hardware | {{HARDWARE}} |
+
+## Preconditions
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is installed and model `{{MODEL}}` is pulled.
+3. Confirm Docker Desktop or Engine is installed.
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+\`\`\`bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+\`\`\`
+
+Install uv if missing:
+
+\`\`\`bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+\`\`\`
+
+Fail if \`ollama\` or \`docker\` is missing.
+
+## Step 2 — native Ollama health
+
+\`\`\`bash
+curl -sf {{OLLAMA_ENDPOINT}}/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "{{MODEL}}"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+\`\`\`
+
+If the model is missing:
+
+\`\`\`bash
+ollama pull {{MODEL}}
+\`\`\`
+
+## Step 3 — clone repos
+
+\`\`\`bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+git clone {{MAIN_REPO}}.git open-autoagent
+git clone {{DOMAIN_REPO}}.git secure-torrent-mcp-agent
+cd "$SRC/open-autoagent"
+git checkout main && git pull
+git checkout -b {{DOMAIN_BRANCH}} || git checkout {{DOMAIN_BRANCH}}
+
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+\`\`\`
+
+## Step 4 — write \`.env\`
+
+\`\`\`bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL={{MODEL}}
+LLM_BASE_URL={{OLLAMA_ENDPOINT}}
+OLLAMA_API_BASE={{OLLAMA_ENDPOINT}}
+EOF
+
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a && . ./.env && set +a
+\`\`\`
+
+## Step 5 — Python env and Docker base image
+
+\`\`\`bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+\`\`\`
+
+Confirm the agent module imports:
+
+\`\`\`bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("import_ok")
+PY
+\`\`\`
+
+## Step 6 — first Harbor run (baseline)
+
+\`\`\`bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1 || true
+\`\`\`
+
+Check output:
+
+\`\`\`bash
+tail -n 40 run.log
+ls jobs | head
+\`\`\`
+
+## Done
+
+The setup is complete when:
+- Ollama returns the model tag
+- Docker base image built successfully
+- Agent module imports with the correct provider and model
+- At least one Harbor command ran (even if tasks don't exist yet)
+
+Next: Point a coding agent at \`program.md\` to run experiments.
diff --git a/setup/configure.ps1 b/setup/configure.ps1
new file mode 100644
index 00000000..367ead0f
--- /dev/null
+++ b/setup/configure.ps1
@@ -0,0 +1,87 @@
+#Requires -Version 5.1
+<#
+.SYNOPSIS
+    Configure setup options for the open-autoagent-ollama-setup skill.
+.DESCRIPTION
+    Interactively collects repository, model, and hardware information,
+    then generates a customized SKILL.md template. Run this BEFORE install.ps1
+    if you want to use a custom repo, model, or hardware profile.
+
+    Output: setup/.skill-config.json (gitignored, used by install.ps1)
+.EXAMPLE
+    .\setup\configure.ps1
+#>
+
+$ErrorActionPreference = "Stop"
+
+$ScriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
+$ConfigFile = Join-Path $ScriptDir ".skill-config.json"
+
+# Defaults (sensible for the original use case)
+$defaults = @{
+    mainRepo = "https://github.com/Oncorporation/open-autoagent"
+    domainRepo = "https://github.com/Oncorporation/secure-torrent-mcp-agent"
+    domainBranch = "domain/secure-torrent"
+    llmProvider = "ollama"
+    model = "qwen3.8:27b-mtp-q8_0"
+    ollamaEndpoint = "http://127.0.0.1:11434"
+    hardware = "AMD Ryzen AI Max+ 395 64GB-64GB"
+}
+
+Write-Host ""
+Write-Host "  open-autoagent-ollama-setup  --  Configuration" -ForegroundColor Cyan
+Write-Host "  -----------------------------------------------" -ForegroundColor DarkGray
+Write-Host ""
+Write-Host "  Press Enter to accept defaults (shown in brackets)" -ForegroundColor DarkGray
+Write-Host ""
+
+# Main repo
+$prompt = "  Main repository URL"
+$default = $defaults.mainRepo
+$input = (Read-Host "$prompt [$default]").Trim()
+$config = @{ mainRepo = if ($input) { $input } else { $default } }
+
+# Domain repo (optional)
+$prompt = "  Domain/catalog repository URL (leave blank to skip)"
+$default = $defaults.domainRepo
+$input = (Read-Host "$prompt [$default]").Trim()
+$config.domainRepo = if ($input) { $input } else { $default }
+
+$prompt = "  Domain branch name"
+$default = $defaults.domainBranch
+$input = (Read-Host "$prompt [$default]").Trim()
+$config.domainBranch = if ($input) { $input } else { $default }
+
+# LLM provider
+$prompt = "  LLM provider (ollama, openai, anthropic, azure)"
+$default = $defaults.llmProvider
+$input = (Read-Host "$prompt [$default]").Trim()
+$config.llmProvider = if ($input) { $input } else { $default }
+
+# Model
+$prompt = "  Model name"
+$default = $defaults.model
+$input = (Read-Host "$prompt [$default]").Trim()
+$config.model = if ($input) { $input } else { $default }
+
+# Ollama endpoint (only if ollama provider)
+if ($config.llmProvider -eq "ollama") {
+    $prompt = "  Ollama endpoint"
+    $default = $defaults.ollamaEndpoint
+    $input = (Read-Host "$prompt [$default]").Trim()
+    $config.ollamaEndpoint = if ($input) { $input } else { $default }
+}
+
+# Hardware
+$prompt = "  Hardware profile (optional, for notes only)"
+$default = $defaults.hardware
+$input = (Read-Host "$prompt [$default]").Trim()
+$config.hardware = if ($input) { $input } else { $default }
+
+# Save config
+$config | ConvertTo-Json | Out-File -Encoding UTF8 $ConfigFile
+Write-Host ""
+Write-Host "  ✓ Saved to: $ConfigFile" -ForegroundColor Green
+Write-Host ""
+Write-Host "  Next: run .\setup\install.ps1" -ForegroundColor Cyan
+Write-Host ""
diff --git a/setup/configure.sh b/setup/configure.sh
new file mode 100644
index 00000000..f18d04c9
--- /dev/null
+++ b/setup/configure.sh
@@ -0,0 +1,71 @@
+#!/usr/bin/env bash
+# configure.sh — Configure setup options for the open-autoagent-ollama-setup skill.
+#
+# Interactively collects repository, model, and hardware information,
+# then generates a customized SKILL.md template. Run this BEFORE install.sh
+# if you want to use a custom repo, model, or hardware profile.
+#
+# Output: setup/.skill-config.json (gitignored, used by install.sh)
+#
+# Usage:  bash setup/configure.sh
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+CONFIG_FILE="$SCRIPT_DIR/.skill-config.json"
+
+# Defaults (sensible for the original use case)
+MAIN_REPO_DEFAULT="https://github.com/Oncorporation/open-autoagent"
+DOMAIN_REPO_DEFAULT="https://github.com/Oncorporation/secure-torrent-mcp-agent"
+DOMAIN_BRANCH_DEFAULT="domain/secure-torrent"
+LLM_PROVIDER_DEFAULT="ollama"
+MODEL_DEFAULT="qwen3.8:27b-mtp-q8_0"
+OLLAMA_ENDPOINT_DEFAULT="http://127.0.0.1:11434"
+HARDWARE_DEFAULT="AMD Ryzen AI Max+ 395 64GB-64GB"
+
+echo ""
+echo "  open-autoagent-ollama-setup  --  Configuration"
+echo "  -----------------------------------------------"
+echo ""
+echo "  Press Enter to accept defaults (shown in brackets)"
+echo ""
+
+# Helper: read with default
+read_with_default() {
+    local prompt="$1"
+    local default="$2"
+    read -rp "  $prompt [$default]: " input
+    echo "${input:-$default}"
+}
+
+# Gather config
+MAIN_REPO=$(read_with_default "Main repository URL" "$MAIN_REPO_DEFAULT")
+DOMAIN_REPO=$(read_with_default "Domain/catalog repository URL" "$DOMAIN_REPO_DEFAULT")
+DOMAIN_BRANCH=$(read_with_default "Domain branch name" "$DOMAIN_BRANCH_DEFAULT")
+LLM_PROVIDER=$(read_with_default "LLM provider (ollama, openai, anthropic, azure)" "$LLM_PROVIDER_DEFAULT")
+MODEL=$(read_with_default "Model name" "$MODEL_DEFAULT")
+
+if [[ "$LLM_PROVIDER" == "ollama" ]]; then
+    OLLAMA_ENDPOINT=$(read_with_default "Ollama endpoint" "$OLLAMA_ENDPOINT_DEFAULT")
+fi
+
+HARDWARE=$(read_with_default "Hardware profile (optional, for notes only)" "$HARDWARE_DEFAULT")
+
+# Build JSON
+cat > "$CONFIG_FILE" << EOF
+{
+  "mainRepo": "$MAIN_REPO",
+  "domainRepo": "$DOMAIN_REPO",
+  "domainBranch": "$DOMAIN_BRANCH",
+  "llmProvider": "$LLM_PROVIDER",
+  "model": "$MODEL",
+  "ollamaEndpoint": "${OLLAMA_ENDPOINT:-}",
+  "hardware": "$HARDWARE"
+}
+EOF
+
+echo ""
+echo "  ✓ Saved to: $CONFIG_FILE"
+echo ""
+echo "  Next: bash setup/install.sh"
+echo ""
diff --git a/setup/harness/claude-code/SKILL.md b/setup/harness/claude-code/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/claude-code/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/harness/claude-desktop/SKILL.md b/setup/harness/claude-desktop/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/claude-desktop/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/harness/cursor/SKILL.md b/setup/harness/cursor/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/cursor/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/harness/grok/SKILL.md b/setup/harness/grok/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/grok/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/harness/hermes/SKILL.md b/setup/harness/hermes/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/hermes/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/harness/visual-studio/SKILL.md b/setup/harness/visual-studio/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/visual-studio/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/harness/vscode/SKILL.md b/setup/harness/vscode/SKILL.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/harness/vscode/SKILL.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.
diff --git a/setup/install.ps1 b/setup/install.ps1
new file mode 100644
index 00000000..87dcb76c
--- /dev/null
+++ b/setup/install.ps1
@@ -0,0 +1,171 @@
+#Requires -Version 5.1
+<#
+.SYNOPSIS
+    Installs the open-autoagent-ollama-setup skill for your AI harness.
+.DESCRIPTION
+    Prompts for harness selection and copies the pre-built SKILL.md to the
+    correct location for that harness. Additional harnesses can be added by
+    creating a subfolder under setup\harness\ and updating the switch below.
+.EXAMPLE
+    .\setup\install.ps1
+#>
+
+$ErrorActionPreference = "Stop"
+
+$ScriptDir  = Split-Path -Parent $MyInvocation.MyCommand.Path
+$RepoRoot   = Split-Path -Parent $ScriptDir
+$HarnessDir = Join-Path $ScriptDir "harness"
+$SkillName  = "open-autoagent-ollama-setup"
+$UserHome   = $env:USERPROFILE
+$ConfigFile = Join-Path $ScriptDir ".skill-config.json"
+
+# Load config if it exists
+if (Test-Path $ConfigFile) {
+    $config = Get-Content -Raw $ConfigFile | ConvertFrom-Json
+    $mainRepo = $config.mainRepo
+    $model = $config.model
+    $ollamaEndpoint = $config.ollamaEndpoint
+    $hardware = $config.hardware
+    $domainRepo = $config.domainRepo
+    $domainBranch = $config.domainBranch
+} else {
+    # Defaults
+    $mainRepo = "https://github.com/Oncorporation/open-autoagent"
+    $model = "qwen3.8:27b-mtp-q8_0"
+    $ollamaEndpoint = "http://127.0.0.1:11434"
+    $hardware = "AMD Ryzen AI Max+ 395 64GB-64GB"
+    $domainRepo = "https://github.com/Oncorporation/secure-torrent-mcp-agent"
+    $domainBranch = "domain/secure-torrent"
+}
+
+# ── menu ──────────────────────────────────────────────────────────────────────
+Write-Host ""
+Write-Host "  open-autoagent-ollama-setup  --  Skill Installer" -ForegroundColor Cyan
+Write-Host "  --------------------------------------------------" -ForegroundColor DarkGray
+Write-Host ""
+Write-Host "  Select your AI harness:" -ForegroundColor White
+Write-Host "    1) Hermes"
+Write-Host "    2) Claude Code         (project-level: <repo>\.claude\)"
+Write-Host "    3) Claude Desktop      (user-level: ~\.claude\)"
+Write-Host "    4) Cursor              (project-level: <repo>\.cursor\)"
+Write-Host "    5) Grok                (user-level: ~\.grok\)"
+Write-Host "    6) VS Code + Copilot   (project-level: <repo>\.vscode\)"
+Write-Host "    7) Visual Studio       (project-level: <repo>\.github\)"
+Write-Host ""
+Write-Host "  (Additional harnesses: add a folder under setup\harness\ and re-run)" -ForegroundColor DarkGray
+Write-Host ""
+
+$choice = ""
+while ($choice -notmatch '^[1-7]$') {
+    $choice = (Read-Host "  Enter number [1-7]").Trim()
+}
+
+# ── resolve harness name and install path ─────────────────────────────────────
+switch ($choice) {
+    "1" {
+        $Harness   = "hermes"
+        $TargetDir = Join-Path $UserHome ".hermes\skills\mcp-install\$SkillName"
+    }
+    "2" {
+        $Harness   = "claude-code"
+        $TargetDir = Join-Path $RepoRoot ".claude\skills\$SkillName"
+    }
+    "3" {
+        $Harness   = "claude-desktop"
+        $TargetDir = Join-Path $UserHome ".claude\skills\$SkillName"
+    }
+    "4" {
+        $Harness   = "cursor"
+        $TargetDir = Join-Path $RepoRoot ".cursor\skills\$SkillName"
+    }
+    "5" {
+        $Harness   = "grok"
+        $TargetDir = Join-Path $UserHome ".grok\skills\$SkillName"
+    }
+    "6" {
+        $Harness   = "vscode"
+        $TargetDir = Join-Path $RepoRoot ".vscode\skills\$SkillName"
+    }
+    "7" {
+        $Harness   = "visual-studio"
+        $TargetDir = Join-Path $RepoRoot ".github\skills\$SkillName"
+    }
+}
+
+# ── locate and process source ────────────────────────────────────────────────
+$SourceFile = Join-Path $HarnessDir "$Harness\SKILL.md"
+
+# Fall back to template-based generation if no harness-specific file exists
+if (-not (Test-Path $SourceFile)) {
+    $Template = Join-Path $ScriptDir "SKILL.md.template"
+    if (-not (Test-Path $Template)) {
+        # Further fallback: use canonical if template missing
+        $SourceFile = Join-Path $ScriptDir "$SkillName.md"
+    } else {
+        # Generate from template on-the-fly
+        $TempFile = Join-Path $env:TEMP "skill-$Harness-$(Get-Random).md"
+        $TemplateContent = Get-Content -Raw $Template
+        $TemplateContent = $TemplateContent -replace '\{\{MAIN_REPO\}\}', $mainRepo
+        $TemplateContent = $TemplateContent -replace '\{\{MODEL\}\}', $model
+        $TemplateContent = $TemplateContent -replace '\{\{OLLAMA_ENDPOINT\}\}', $ollamaEndpoint
+        $TemplateContent = $TemplateContent -replace '\{\{HARDWARE\}\}', $hardware
+        $TemplateContent = $TemplateContent -replace '\{\{DOMAIN_REPO\}\}', $domainRepo
+        $TemplateContent = $TemplateContent -replace '\{\{DOMAIN_BRANCH\}\}', $domainBranch
+        Set-Content -Path $TempFile -Value $TemplateContent
+        $SourceFile = $TempFile
+    }
+}
+
+if (-not (Test-Path $SourceFile)) {
+    Write-Error "Source SKILL.md not found at '$SourceFile'."
+    exit 1
+}
+
+# ── confirm ───────────────────────────────────────────────────────────────────
+Write-Host ""
+Write-Host "  Harness : $Harness" -ForegroundColor Yellow
+Write-Host "  Source  : $SourceFile" -ForegroundColor DarkGray
+Write-Host "  Target  : $TargetDir\SKILL.md" -ForegroundColor Yellow
+Write-Host "  Model   : $model" -ForegroundColor DarkGray
+Write-Host "  Repo    : $mainRepo" -ForegroundColor DarkGray
+Write-Host ""
+
+$confirm = (Read-Host "  Proceed? [Y/n]").Trim()
+if ($confirm -match '^[Nn]') {
+    Write-Host "  Aborted." -ForegroundColor Red
+    exit 0
+}
+
+# ── install ───────────────────────────────────────────────────────────────────
+New-Item -ItemType Directory -Force -Path $TargetDir | Out-Null
+Copy-Item -Path $SourceFile -Destination (Join-Path $TargetDir "SKILL.md") -Force
+
+# Clean up temp file if created
+if ($SourceFile -match '\\Temp\\') {
+    Remove-Item -Path $SourceFile -Force
+}
+
+Write-Host ""
+Write-Host "  ✓ Installed: $TargetDir\SKILL.md" -ForegroundColor Green
+Write-Host ""
+
+# ── trigger instructions ──────────────────────────────────────────────────────
+Write-Host "  Next: open $Harness and run the skill:" -ForegroundColor Cyan
+switch ($Harness) {
+    "hermes"         { Write-Host "    Start a new session (or /reset), then paste:" ; Write-Host "      run open-autoagent-ollama-setup" }
+    "claude-code"    { Write-Host "    /skill open-autoagent-ollama-setup" }
+    "claude-desktop" { Write-Host "    run the skill named open-autoagent-ollama-setup" }
+    "cursor"         { Write-Host "    @open-autoagent-ollama-setup  in the Cursor chat" }
+    "grok"           { Write-Host "    run open-autoagent-ollama-setup" }
+    "vscode"         {
+        Write-Host "    In Copilot Chat (Ctrl+Shift+I), attach the file then ask:"
+        Write-Host "      #file:.vscode\skills\$SkillName\SKILL.md"
+        Write-Host "      run open-autoagent-ollama-setup"
+    }
+    "visual-studio"  {
+        Write-Host "    In Copilot Chat (View > GitHub Copilot Chat), attach the file then ask:"
+        Write-Host "      #file:.github\skills\$SkillName\SKILL.md"
+        Write-Host "      run open-autoagent-ollama-setup"
+    }
+}
+Write-Host ""
diff --git a/setup/install.sh b/setup/install.sh
new file mode 100644
index 00000000..56b168ff
--- /dev/null
+++ b/setup/install.sh
@@ -0,0 +1,155 @@
+#!/usr/bin/env bash
+# install.sh — Install open-autoagent-ollama-setup skill for your AI harness.
+#
+# Usage:  bash setup/install.sh
+#         (or chmod +x setup/install.sh && ./setup/install.sh from repo root)
+#
+# Additional harnesses: add a subfolder under setup/harness/ and update the
+# case block below.
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REPO_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
+HARNESS_DIR="$SCRIPT_DIR/harness"
+SKILL_NAME="open-autoagent-ollama-setup"
+CONFIG_FILE="$SCRIPT_DIR/.skill-config.json"
+
+# Load config if it exists
+if [[ -f "$CONFIG_FILE" ]]; then
+    MAIN_REPO=$(jq -r '.mainRepo // empty' "$CONFIG_FILE")
+    MODEL=$(jq -r '.model // empty' "$CONFIG_FILE")
+    OLLAMA_ENDPOINT=$(jq -r '.ollamaEndpoint // empty' "$CONFIG_FILE")
+    HARDWARE=$(jq -r '.hardware // empty' "$CONFIG_FILE")
+    DOMAIN_REPO=$(jq -r '.domainRepo // empty' "$CONFIG_FILE")
+    DOMAIN_BRANCH=$(jq -r '.domainBranch // empty' "$CONFIG_FILE")
+else
+    # Defaults
+    MAIN_REPO="https://github.com/Oncorporation/open-autoagent"
+    MODEL="qwen3.8:27b-mtp-q8_0"
+    OLLAMA_ENDPOINT="http://127.0.0.1:11434"
+    HARDWARE="AMD Ryzen AI Max+ 395 64GB-64GB"
+    DOMAIN_REPO="https://github.com/Oncorporation/secure-torrent-mcp-agent"
+    DOMAIN_BRANCH="domain/secure-torrent"
+fi
+
+# ── menu ──────────────────────────────────────────────────────────────────────
+echo ""
+echo "  open-autoagent-ollama-setup  --  Skill Installer"
+echo "  --------------------------------------------------"
+echo ""
+echo "  Select your AI harness:"
+echo "    1) Hermes"
+echo "    2) Claude Code         (project-level: <repo>/.claude/)"
+echo "    3) Claude Desktop      (user-level: ~/.claude/)"
+echo "    4) Cursor              (project-level: <repo>/.cursor/)"
+echo "    5) Grok                (user-level: ~/.grok/)"
+echo "    6) VS Code + Copilot   (project-level: <repo>/.vscode/)"
+echo "    7) Visual Studio       (project-level: <repo>/.github/)"
+echo ""
+echo "  (Additional harnesses: add a folder under setup/harness/ and re-run)"
+echo ""
+
+choice=""
+while [[ ! "$choice" =~ ^[1-7]$ ]]; do
+    read -rp "  Enter number [1-7]: " choice
+done
+
+# ── resolve harness name and install path ─────────────────────────────────────
+case "$choice" in
+    1) HARNESS="hermes";         TARGET_DIR="$HOME/.hermes/skills/mcp-install/$SKILL_NAME" ;;
+    2) HARNESS="claude-code";    TARGET_DIR="$REPO_ROOT/.claude/skills/$SKILL_NAME" ;;
+    3) HARNESS="claude-desktop"; TARGET_DIR="$HOME/.claude/skills/$SKILL_NAME" ;;
+    4) HARNESS="cursor";         TARGET_DIR="$REPO_ROOT/.cursor/skills/$SKILL_NAME" ;;
+    5) HARNESS="grok";           TARGET_DIR="$HOME/.grok/skills/$SKILL_NAME" ;;
+    6) HARNESS="vscode";         TARGET_DIR="$REPO_ROOT/.vscode/skills/$SKILL_NAME" ;;
+    7) HARNESS="visual-studio";  TARGET_DIR="$REPO_ROOT/.github/skills/$SKILL_NAME" ;;
+esac
+
+# ── locate and process source ────────────────────────────────────────────────
+TEMPLATE_FILE="$HARNESS_DIR/$HARNESS/SKILL.md"
+HARNESS_SOURCE_FILE="$TEMPLATE_FILE"
+
+# Fall back to template-based generation if no harness-specific file exists
+if [[ ! -f "$HARNESS_SOURCE_FILE" ]]; then
+    TEMPLATE="$SCRIPT_DIR/SKILL.md.template"
+    if [[ ! -f "$TEMPLATE" ]]; then
+        # Further fallback: use canonical if template missing
+        HARNESS_SOURCE_FILE="$SCRIPT_DIR/$SKILL_NAME.md"
+    else
+        # Generate from template on-the-fly
+        HARNESS_SOURCE_FILE="/tmp/$SKILL_NAME-$HARNESS-$RANDOM.md"
+        sed \
+            -e "s|{{MAIN_REPO}}|$MAIN_REPO|g" \
+            -e "s|{{MODEL}}|$MODEL|g" \
+            -e "s|{{OLLAMA_ENDPOINT}}|$OLLAMA_ENDPOINT|g" \
+            -e "s|{{HARDWARE}}|$HARDWARE|g" \
+            -e "s|{{DOMAIN_REPO}}|$DOMAIN_REPO|g" \
+            -e "s|{{DOMAIN_BRANCH}}|$DOMAIN_BRANCH|g" \
+            "$TEMPLATE" > "$HARNESS_SOURCE_FILE"
+    fi
+fi
+
+if [[ ! -f "$HARNESS_SOURCE_FILE" ]]; then
+    echo "ERROR: No source SKILL.md found and no template to process." >&2
+    exit 1
+fi
+
+# ── confirm ───────────────────────────────────────────────────────────────────
+echo ""
+echo "  Harness : $HARNESS"
+echo "  Source  : $HARNESS_SOURCE_FILE"
+echo "  Target  : $TARGET_DIR/SKILL.md"
+echo "  Model   : $MODEL"
+echo "  Repo    : $MAIN_REPO"
+echo ""
+read -rp "  Proceed? [Y/n]: " confirm
+if [[ "$confirm" =~ ^[Nn] ]]; then
+    echo "  Aborted."
+    exit 0
+fi
+
+# ── install ───────────────────────────────────────────────────────────────────
+mkdir -p "$TARGET_DIR"
+cp -f "$HARNESS_SOURCE_FILE" "$TARGET_DIR/SKILL.md"
+
+# Clean up temp file if created
+if [[ "$HARNESS_SOURCE_FILE" =~ ^/tmp/ ]]; then
+    rm -f "$HARNESS_SOURCE_FILE"
+fi
+
+echo ""
+echo "  ✓ Installed: $TARGET_DIR/SKILL.md"
+echo ""
+
+# ── trigger instructions ──────────────────────────────────────────────────────
+echo "  Next: open $HARNESS and run the skill:"
+case "$HARNESS" in
+    hermes)
+        echo "    Start a new session (or /reset), then paste:"
+        echo "      run open-autoagent-ollama-setup"
+        ;;
+    claude-code)
+        echo "    /skill open-autoagent-ollama-setup"
+        ;;
+    claude-desktop)
+        echo "    run the skill named open-autoagent-ollama-setup"
+        ;;
+    cursor)
+        echo "    @open-autoagent-ollama-setup  in the Cursor chat"
+        ;;
+    grok)
+        echo "    run open-autoagent-ollama-setup"
+        ;;
+    vscode)
+        echo "    In Copilot Chat (Ctrl+Shift+I), attach the file then ask:"
+        echo "      #file:.vscode/skills/$SKILL_NAME/SKILL.md"
+        echo "      run open-autoagent-ollama-setup"
+        ;;
+    visual-studio)
+        echo "    In Copilot Chat (View > GitHub Copilot Chat), attach the file then ask:"
+        echo "      #file:.github/skills/$SKILL_NAME/SKILL.md"
+        echo "      run open-autoagent-ollama-setup"
+        ;;
+esac
+echo ""
diff --git a/setup/open-autoagent-ollama-setup.md b/setup/open-autoagent-ollama-setup.md
new file mode 100644
index 00000000..d14f0248
--- /dev/null
+++ b/setup/open-autoagent-ollama-setup.md
@@ -0,0 +1,437 @@
+---
+name: open-autoagent-ollama-setup
+description: Set up Oncorporation open-autoagent on a host-native Ollama daemon for Harbor harness experiments. Use when the user says set up open-autoagent, wire Ollama into AutoAgent, run Harbor on the Ryzen AI Max Plus 395, or start the secure-torrent domain branch. Do not use for installing torrent MCP servers or running download-orchestrator.
+license: MIT
+metadata:
+  hermes:
+    tags:
+      - open-autoagent
+      - ollama
+      - harbor
+      - harness
+    category: mcp-install
+  version: "1.0.0"
+  hardware: AMD Ryzen AI Max+ 395 64GB-64GB
+  ollama_model: qwen3.8:27b-mtp-q8_0
+---
+
+# Set up open-autoagent on host-native Ollama
+
+You are running this procedure on the operator machine. Execute the steps
+in order. Stop on the first failed check. Do not skip smoke tests. Do not
+put Ollama in Docker. Do not point LiteLLM at `host.docker.internal`.
+
+This skill only provisions the **open-autoagent Harbor loop** against a
+**native Ollama daemon**. Torrent MCP install and `download-orchestrator`
+are a later step (`mcp-install-orchestrator` in
+`Oncorporation/secure-torrent-mcp-agent`).
+
+## Locked settings from the project session
+
+Treat these as the source of truth unless the operator explicitly overrides
+them in the current turn.
+
+| Key | Value |
+|---|---|
+| Repo | `https://github.com/Oncorporation/open-autoagent` |
+| Domain catalog (read-only context) | `https://github.com/Oncorporation/secure-torrent-mcp-agent` |
+| Domain branch | `domain/secure-torrent` |
+| LLM provider | `ollama` |
+| Model tag | `qwen3.8:27b-mtp-q8_0` |
+| LiteLLM model string | `ollama_chat/qwen3.8:27b-mtp-q8_0` |
+| Ollama bind | `http://127.0.0.1:11434` |
+| `LLM_BASE_URL` | `http://127.0.0.1:11434` (no `/v1`) |
+| `OLLAMA_API_BASE` | `http://127.0.0.1:11434` |
+| Ollama runtime | native host process, not a container |
+| Hardware | AMD Ryzen AI Max+ 395, 64 GB CPU / 64 GB iGPU split |
+| Harbor concurrency | `-n 1` |
+| Agent context target | 16K–32K, never 256K for these loops |
+| Thinking | off for tool loops |
+| Docker role | Harbor task sandbox only |
+
+Legal constraint for any torrent-domain task you create later — authorized
+fetches only (Linux ISOs, public domain, content the operator may fetch).
+Eval fixtures only. No live indexer or copyrighted-title tasks.
+
+## Preconditions to collect
+
+Ask only if missing. Do not invent paths.
+
+1. Workspace parent. Default `~/src`.
+2. Confirm Ollama is already installed and the model tag above is pulled.
+3. Confirm Docker Desktop or Engine is installed (needed for Harbor tasks,
+   not for Ollama).
+4. Confirm `git`, `curl`, and Python 3.10+ exist.
+
+If the operator is on Windows, use Git Bash or an equivalent Unix shell.
+PowerShell translation is allowed only for path separators.
+
+## Step 0 — refuse the wrong job
+
+If the operator asked to install qBittorrent / Transmission / ClamAV MCP
+servers, stop and say this skill is the wrong one. Point them at
+`mcp-install-orchestrator`.
+
+If they asked to run `download-orchestrator` against a live client, stop.
+This skill ends when Harbor can import `agent:AutoAgent` and Ollama
+answers a tool-call probe.
+
+## Step 1 — host toolchain
+
+Run and record output.
+
+```bash
+uname -a
+command -v git
+command -v curl
+command -v python3
+command -v docker
+command -v uv || true
+command -v ollama
+ollama --version
+docker version --format '{{.Server.Version}}' 2>/dev/null || docker version
+```
+
+Install uv if missing:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Fail if `ollama` or `docker` is missing. Do not install Ollama inside
+Docker to paper over that.
+
+## Step 2 — native Ollama health
+
+```bash
+curl -sf http://127.0.0.1:11434/api/tags >/tmp/ollama-tags.json
+python3 - << 'PY'
+import json
+tags = json.load(open("/tmp/ollama-tags.json"))
+names = [m.get("name") for m in tags.get("models", [])]
+print("models:", names)
+need = "qwen3.8:27b-mtp-q8_0"
+ok = any(n == need or n.startswith(need) for n in names)
+print("have_target:", ok)
+raise SystemExit(0 if ok else 2)
+PY
+```
+
+If the model is missing:
+
+```bash
+ollama pull qwen3.8:27b-mtp-q8_0
+```
+
+Placement check (must be iGPU, not a CPU-only dump):
+
+```bash
+ollama run qwen3.8:27b-mtp-q8_0 "reply with the single word ok"
+ollama ps
+```
+
+`PROCESSOR` / `GPU` columns must show the model resident on GPU. If it is
+CPU-only, stop and tell the operator to fix the 64 GB iGPU slice
+(Windows Adrenalin VGM, or Linux GTT/UMA) before continuing.
+
+Tool-call probe with thinking disabled:
+
+```bash
+curl -sf http://127.0.0.1:11434/api/chat -o /tmp/ollama-tool.json -d '{
+  "model": "qwen3.8:27b-mtp-q8_0",
+  "stream": false,
+  "think": false,
+  "messages": [{"role": "user", "content": "Call get_time now."}],
+  "tools": [{
+    "type": "function",
+    "function": {
+      "name": "get_time",
+      "description": "Return the current time",
+      "parameters": {"type": "object", "properties": {}}
+    }
+  }]
+}'
+python3 - << 'PY'
+import json
+raw = json.load(open("/tmp/ollama-tool.json"))
+msg = raw.get("message") or {}
+print("keys:", sorted(raw.keys()))
+print("has_tool_calls:", bool(msg.get("tool_calls")))
+print("content_preview:", (msg.get("content") or "")[:240])
+if not msg.get("tool_calls"):
+    raise SystemExit("Ollama did not return tool_calls. Do not start Harbor yet.")
+print("ok")
+PY
+```
+
+If this probe fails, do not proceed to Harbor. Report the JSON and stop.
+
+## Step 3 — clone repos
+
+```bash
+SRC="${SRC:-$HOME/src}"
+mkdir -p "$SRC"
+cd "$SRC"
+
+if [ ! -d open-autoagent/.git ]; then
+  git clone https://github.com/Oncorporation/open-autoagent.git
+fi
+if [ ! -d secure-torrent-mcp-agent/.git ]; then
+  git clone https://github.com/Oncorporation/secure-torrent-mcp-agent.git
+fi
+
+cd "$SRC/open-autoagent"
+git fetch origin
+git checkout main
+git pull --ff-only origin main || true
+```
+
+Create the domain branch if it does not exist:
+
+```bash
+cd "$SRC/open-autoagent"
+if git rev-parse --verify domain/secure-torrent >/dev/null 2>&1; then
+  git checkout domain/secure-torrent
+else
+  git checkout -b domain/secure-torrent
+fi
+```
+
+Vendor the catalog as read-only context. Do not copy it into
+`~/.hermes/skills/` from this skill.
+
+```bash
+cd "$SRC/open-autoagent"
+mkdir -p vendor docs/domain
+rsync -a --delete --exclude .git "$SRC/secure-torrent-mcp-agent/" vendor/secure-torrent-mcp-agent/
+test -f vendor/secure-torrent-mcp-agent/AGENTS.md
+test -f vendor/secure-torrent-mcp-agent/workflows/download-then-scan.md
+```
+
+## Step 4 — write `.env` (never commit)
+
+```bash
+cd "$SRC/open-autoagent"
+cat > .env << 'EOF'
+LLM_PROVIDER=ollama
+MODEL=qwen3.8:27b-mtp-q8_0
+LLM_BASE_URL=http://127.0.0.1:11434
+OLLAMA_API_BASE=http://127.0.0.1:11434
+EOF
+
+# belt and suspenders for shells that do not auto-load .env
+if ! grep -q '^\.env$' .gitignore 2>/dev/null; then
+  printf '\n.env\nresults.tsv\njobs/\nrun.log\n' >> .gitignore
+fi
+
+set -a
+# shellcheck disable=SC1091
+. ./.env
+set +a
+```
+
+Verify `agent.py` still builds `ollama_chat/{MODEL}` when
+`LLM_PROVIDER=ollama`. If it does not, stop and show the `create_agent`
+block. Do not invent a second model router.
+
+## Step 5 — patch `program.md`
+
+Read `program.md`. Apply all of the following. Keep the experiment loop,
+`results.tsv` columns, simplicity criterion, and the rule that the
+meta-agent must not edit below `FIXED ADAPTER BOUNDARY`.
+
+Replace the generic directive with:
+
+```markdown
+## Directive
+
+Build an autonomous download-then-scan harness for authorized torrent
+fetches, matching vendor/secure-torrent-mcp-agent.
+
+Orchestrator split (do not collapse):
+- download-orchestrator (no direct torrent/scanner MCP calls)
+- torrent-subagent (search, present choices, add one item, return path)
+- malware-scan-subagent (scan only named paths)
+
+Rules:
+- Ask before adding when more than one plausible hit exists.
+- Scan named paths only.
+- Never mark a file safe if ClamAV (or the mock scanner) did not run.
+- Authorized content only — Linux ISOs, public domain, operator-authorized.
+  Refuse everything else.
+- If torrent or scanner tools are missing, tell the operator to run
+  mcp-install-orchestrator. Do not invent servers.
+
+Model lock:
+- LLM_PROVIDER=ollama
+- MODEL=qwen3.8:27b-mtp-q8_0
+- Endpoint http://127.0.0.1:11434
+- Do not switch to a cloud model.
+- Thinking off for tool loops.
+- Harbor concurrency 1.
+
+Evaluation is Harbor task score (passed, avg_score).
+The first run is always the unmodified baseline.
+```
+
+Delete any sentence that forbids changing the model away from `gpt-5`.
+
+If `program.md` tells the meta-agent to use `-n 100`, change that example
+to `-n 1`.
+
+## Step 6 — Python env and base image
+
+```bash
+cd "$SRC/open-autoagent"
+uv sync
+docker build -f Dockerfile.base -t autoagent-base .
+```
+
+Confirm the agent module imports on the host (this is where LiteLLM
+calls Ollama):
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+uv run python - << 'PY'
+import os
+print("LLM_PROVIDER", os.environ.get("LLM_PROVIDER"))
+print("MODEL", os.environ.get("MODEL"))
+print("LLM_BASE_URL", os.environ.get("LLM_BASE_URL"))
+import agent
+print("agent.LLM_PROVIDER", agent.LLM_PROVIDER)
+print("agent.MODEL", agent.MODEL)
+print("agent.LLM_BASE_URL", agent.LLM_BASE_URL)
+print("import_ok")
+PY
+```
+
+Expected: provider `ollama`, model `qwen3.8:27b-mtp-q8_0`, base
+`http://127.0.0.1:11434`.
+
+## Step 7 — tasks directory
+
+`open-autoagent` ships without tasks. Harbor cannot score an empty
+`tasks/` tree.
+
+If `tasks/` already has Harbor tasks, list them and skip scaffolding.
+
+If `tasks/` is empty, create **one** smoke task so the loop can run.
+Do not create live BitTorrent tasks.
+
+```text
+tasks/choose-before-add/
+  task.toml
+  instruction.md
+  tests/test.sh
+  tests/test.py
+  environment/Dockerfile
+  files/search_hits.json
+```
+
+`instruction.md` — search for an authorized Debian netinst fixture.
+Two mock hits exist. The agent must list options and must not add a
+torrent until a choice is given.
+
+`files/search_hits.json` — two legal fixture rows (name, size, seeders,
+magnet placeholders). No copyrighted titles.
+
+`environment/Dockerfile`:
+
+```dockerfile
+FROM autoagent-base
+COPY files/search_hits.json /opt/fixture/search_hits.json
+```
+
+`tests/test.sh` must write a 0.0–1.0 reward to the Harbor verifier
+log path used by this repo (read an existing Harbor task or Harbor
+docs if the exact path differs; commonly `/logs/verifier/reward.txt`
+or the path `test.sh` in upstream Harbor examples uses). Score 1.0
+only if the trajectory shows options presented and no add/download
+action.
+
+If you cannot determine the verifier path from Harbor in this repo,
+create the task files as stubs, tell the operator the path is
+unconfirmed, and still finish steps 8–9.
+
+## Step 8 — first Harbor run (baseline)
+
+```bash
+cd "$SRC/open-autoagent"
+set -a && . ./.env && set +a
+rm -rf jobs
+mkdir -p jobs
+uv run harbor run -p tasks/ --task-name choose-before-add -l 1 -n 1 \
+  --agent-import-path agent:AutoAgent -o jobs --job-name latest \
+  > run.log 2>&1
+```
+
+If `choose-before-add` does not exist, run whatever single task is
+present instead of inventing `-n 100`.
+
+After the run:
+
+```bash
+tail -n 80 run.log
+ls jobs | head
+ollama ps
+```
+
+Diagnose from `run.log` and job trajectories. Common failures:
+
+| Symptom | Fix |
+|---|---|
+| connection refused 11434 | Ollama is not running on the host |
+| tried `host.docker.internal` | revert `.env` to `127.0.0.1` |
+| 404 model | tag mismatch; `ollama list` |
+| long think, no tools | thinking leaked; keep think off; check LiteLLM version |
+| GPU empty, CPU pegged | iGPU slice not 64 GB |
+| Harbor `-n` greater than 1 | rerun with `-n 1` |
+
+## Step 9 — tell the operator how to start the meta-loop
+
+Do not start an unsupervised overnight rewrite unless they ask.
+Give them this exact prompt to paste into a new Hermes session
+started from `$SRC/open-autoagent`:
+
+```text
+Read program.md and vendor/secure-torrent-mcp-agent/AGENTS.md.
+Use the Ollama model in .env (qwen3.8:27b-mtp-q8_0 at 127.0.0.1:11434).
+Establish an unmodified baseline first.
+Then propose one harness change above the FIXED ADAPTER BOUNDARY.
+```
+
+Remind them:
+
+- Edit only above `FIXED ADAPTER BOUNDARY` in `agent.py`.
+- Log every experiment in `results.tsv`.
+- Keep or revert on score, not vibes.
+- Specialized tools beat a single `run_shell`.
+- Do not merge qBittorrent and Transmission into one tool.
+
+## Done criteria
+
+All must be true before you declare success:
+
+- [ ] `curl http://127.0.0.1:11434/api/tags` works
+- [ ] `qwen3.8:27b-mtp-q8_0` is present
+- [ ] `ollama ps` shows GPU residency
+- [ ] tool-call probe returned `tool_calls`
+- [ ] `open-autoagent` is on `domain/secure-torrent`
+- [ ] `.env` has the locked values and is gitignored
+- [ ] `program.md` no longer locks `gpt-5`
+- [ ] `uv sync` and `autoagent-base` image succeeded
+- [ ] `agent` imports with provider `ollama`
+- [ ] at least one Harbor command was attempted or a stub task exists
+
+## What you must not do
+
+- Do not `docker run ollama`.
+- Do not set `LLM_BASE_URL=http://host.docker.internal:11434`.
+- Do not append `/v1` for this LiteLLM Ollama provider.
+- Do not change the model tag unless the operator names a new tag.
+- Do not commit `.env`, Web UI passwords, or `VIRUSTOTAL_API_KEY`.
+- Do not flatten `secure-torrent-mcp-agent` into `~/.hermes/skills/`
+  from this skill.
+- Do not start live downloads or indexer searches as part of setup.

From 731ac067bd92fc6c7c57f93525438be882d0708c Mon Sep 17 00:00:00 2001
From: Charles Fettinger <charles@onacloud.org>
Date: Wed, 26 Aug 2026 13:11:42 -0700
Subject: [PATCH 4/6] Update .gitignore to include .cursor and uv.lock files

---
 .gitignore | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.gitignore b/.gitignore
index c4fe8f5d..0facf8bc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -21,4 +21,7 @@ tasks-sheets-verified/
 tasks-sheets/
 
 dev/
+.cursor/rules/jcodemunch.mdc
+uv.lock
+
 /.vs

From 35a641a62a9f4313398f1900eef34cc756c8b0fb Mon Sep 17 00:00:00 2001
From: Charles Fettinger <charles@onacloud.org>
Date: Wed, 26 Aug 2026 13:45:00 -0700
Subject: [PATCH 5/6] Update success message in configure.ps1 for clarity

---
 setup/configure.ps1 | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup/configure.ps1 b/setup/configure.ps1
index 367ead0f..cc260b62 100644
--- a/setup/configure.ps1
+++ b/setup/configure.ps1
@@ -81,7 +81,7 @@ $config.hardware = if ($input) { $input } else { $default }
 # Save config
 $config | ConvertTo-Json | Out-File -Encoding UTF8 $ConfigFile
 Write-Host ""
-Write-Host "  ✓ Saved to: $ConfigFile" -ForegroundColor Green
+Write-Host "  OK Saved to: $ConfigFile" -ForegroundColor Green
 Write-Host ""
 Write-Host "  Next: run .\setup\install.ps1" -ForegroundColor Cyan
 Write-Host ""

From e625d9014bfe15ecaa9511b37fdafafe6577539b Mon Sep 17 00:00:00 2001
From: Charles Fettinger <charles@onacloud.org>
Date: Wed, 26 Aug 2026 13:45:00 -0700
Subject: [PATCH 6/6] Refactor menu comments for consistency and clarity in
 install.ps1

---
 setup/install.ps1 | 17 ++++++++++-------
 1 file changed, 10 insertions(+), 7 deletions(-)

diff --git a/setup/install.ps1 b/setup/install.ps1
index 87dcb76c..2c2ae340 100644
--- a/setup/install.ps1
+++ b/setup/install.ps1
@@ -38,7 +38,7 @@ if (Test-Path $ConfigFile) {
     $domainBranch = "domain/secure-torrent"
 }
 
-# ── menu ──────────────────────────────────────────────────────────────────────
+# -- menu ----------------------------------------------------------------------
 Write-Host ""
 Write-Host "  open-autoagent-ollama-setup  --  Skill Installer" -ForegroundColor Cyan
 Write-Host "  --------------------------------------------------" -ForegroundColor DarkGray
@@ -60,7 +60,7 @@ while ($choice -notmatch '^[1-7]$') {
     $choice = (Read-Host "  Enter number [1-7]").Trim()
 }
 
-# ── resolve harness name and install path ─────────────────────────────────────
+# -- resolve harness name and install path -------------------------------------
 switch ($choice) {
     "1" {
         $Harness   = "hermes"
@@ -92,7 +92,7 @@ switch ($choice) {
     }
 }
 
-# ── locate and process source ────────────────────────────────────────────────
+# -- locate and process source ------------------------------------------------
 $SourceFile = Join-Path $HarnessDir "$Harness\SKILL.md"
 
 # Fall back to template-based generation if no harness-specific file exists
@@ -121,7 +121,7 @@ if (-not (Test-Path $SourceFile)) {
     exit 1
 }
 
-# ── confirm ───────────────────────────────────────────────────────────────────
+# -- confirm -------------------------------------------------------------------
 Write-Host ""
 Write-Host "  Harness : $Harness" -ForegroundColor Yellow
 Write-Host "  Source  : $SourceFile" -ForegroundColor DarkGray
@@ -136,7 +136,7 @@ if ($confirm -match '^[Nn]') {
     exit 0
 }
 
-# ── install ───────────────────────────────────────────────────────────────────
+# -- install -------------------------------------------------------------------
 New-Item -ItemType Directory -Force -Path $TargetDir | Out-Null
 Copy-Item -Path $SourceFile -Destination (Join-Path $TargetDir "SKILL.md") -Force
 
@@ -146,10 +146,10 @@ if ($SourceFile -match '\\Temp\\') {
 }
 
 Write-Host ""
-Write-Host "  ✓ Installed: $TargetDir\SKILL.md" -ForegroundColor Green
+Write-Host "  OK Installed: $TargetDir\SKILL.md" -ForegroundColor Green
 Write-Host ""
 
-# ── trigger instructions ──────────────────────────────────────────────────────
+# -- trigger instructions ------------------------------------------------------
 Write-Host "  Next: open $Harness and run the skill:" -ForegroundColor Cyan
 switch ($Harness) {
     "hermes"         { Write-Host "    Start a new session (or /reset), then paste:" ; Write-Host "      run open-autoagent-ollama-setup" }
@@ -167,5 +167,8 @@ switch ($Harness) {
         Write-Host "      #file:.github\skills\$SkillName\SKILL.md"
         Write-Host "      run open-autoagent-ollama-setup"
     }
+    default {
+        throw "Unknown harness '$Harness'. Add a folder under setup\harness\ and a matching arm here."
+    }
 }
 Write-Host ""