behavioral-testing

Rebuild software from behavior, not source code. An MCP-powered toolkit for black-box observation, clean-room reimplementation, and behavioral verification.

AgentBehaviorBench (ABB): A benchmark for evaluating AI agents’ ability to test other agents and detect behavioral defects.

Community-driven behavioral reliability benchmark for LLMs. 231 probes across 19 modules, deterministic scoring, perplexity correlation, layer sensitivity mapping, quant method capture, hardware-stratified community rankings. Every test contributes to the community dataset.

Runtime behavioral contracts for AI agents: define YAML contracts, check adapter outputs, and raise explicit contract violations. Agent Behavioral Contracts (ABC).

Execution-grounded semantic clone detection for JS/TS — finds functions that behave the same but are written differently, then runs them in a sandbox to prove which one is wrong.

Prove web features work in a real browser—with persistence, source-of-truth, replay, and CI evidence.

LLM drift detector — know within 5 min when GPT-4o, Claude, or Gemini silently changes behaviour. Open source, self-hostable.

Executable behavioral contracts and hidden-evaluation harness for coding agents across nine software domains.

🩺 Behavioral testing for skill triggers — diagnose why a skill never fires (or fires too often), prescribe a fixed description, save a regression suite. One SKILL.md, 79 agents (Claude Code, Hermes, Codex, Gemini...)

Static analyzer for React tests that finds UI behaviors exercised but not explicitly verified. Testing Library, Jest/Vitest, and Material UI.

Model behavioral diffing - compare LLM outputs across versions, detect regressions.

Behavioral regression testing for AI applications: repeat LLM, agent and RAG test cases, and tell real regressions from noise.

Agent Skill for Claude Code that measures whether coding agents actually follow a skill, rule or agent definition: it generates scenarios from supportive to competing prompts, runs an agent on each, and reports compliance rates with classified tool call timelines.

Behavioral regression testing for LLMs — diff, drift, fingerprint. Zero deps.

Open-source behavioral contract testing for AI agents. Define critical behavior, run the real agent, and catch regressions.

Behavioral browser-spec layer for agent-in-session use. Specs declare intent+outcomes; agents execute + heal via agent-browser or Playwright. CLI + MCP server, agent-neutral.

Regression testing CLI for AI agents — define expected behaviors in YAML, run in CI, fail deploys on behavioral drift

Agent behavioral testing -- YAML specs for tool calls, sequences, constraints

E2E behavioral testing for AI agents — grounded in 24 research papers. pip install agentgate-eval