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feat(scripts): evaluate budgeted task resumption with JEV #89

Description

@ericpaulsen

Evaluate budgeted task resumption with JEV

Sediment exposes grant-scoped evidence inventory, manifests, and exact reads. The earlier required-lookup comparison recovers a historical constraint but uses more input tokens than full-history injection. Its frozen validator also misses quoted embedded CSV newlines. The next experiment measures whether selecting history before the coding agent starts preserves correctness with less context and lower total observed usage.

Decision: implement a separate, private evaluation driver on main after #85. Reuse the isolated pi controller and shipped evidence routes. Compare no history, full captured history, budgeted keyword selection, and JEV selection. Pin JEV 1.13.0 through the official TypeSafe API for the initial adapter. Credential availability gates live JEV execution. Use synthetic task histories; preserve previous fixtures and results.

Deliverables and dependencies

  • T1: Versioned task fixtures and independent validators for required history, unnecessary history, and relevant history mixed with distractors. Include quoted embedded newlines and validator mutation checks. Preserve the original Add agent-requested context retrieval for one previous Session #69 evaluation.
  • T2: Consumer-side factual evidence reads, complete-context byte budgeting, deterministic packing, and a bounded JEV adapter. Reuse existing schemas, keyword policy, and HTTP dependency. Validate versioned responses, allowlisted references, and usage. Count every request, candidate prefetch, refusal, and selector token. No automatic retry or hidden fallback.
  • T3: Frozen 36-run comparison (three profiles, four arms, three repetitions), isolated source capture and fresh continuations, complete private records, capture/trajectory verification, and truthful usage/cost summaries. T3 depends on T1/T2 contracts; integration depends on both implementations.
  • T4: Offline and real API acceptance, live native preflight, one frozen comparison when credentials are available, documentation, independent whole-branch and different-vendor review, and required CI. T4 depends on T1–T3.

Implementation status: 2026-09-23

PR #90 implements T1–T3 at 64a2e9c. All required CI and reviews pass. All 36 continuations finish; the final results report preserves 21 valid original measurements and 15 invalid measurements. Supplemental audits verify reported token usage, capture, and delivery for all 36 Sessions. Final-workspace checks report both-check passes of A 1/9, B 0/9, C 9/9, and D 0/9. JEV provides no historical content and shows no quality-preserving savings.

T4 remains unchecked because the frozen live acceptance remains incomplete. No acceptance amendment or merge is authorized. PR #90 stays draft. Exact original verification traffic counts and bytes remain unknown; the report discloses the premature audit's overlap with two runs. Owned runtime services are stopped after the database archive; private artifacts and the integration branch are retained.

Acceptance

All coding arms use identical model, tools, workspace, visible prompt, and limits. Selection occurs in the experiment consumer at resumption, before the first coding-model request. The history corpus is the final captured call's complete conversation, with preceding-call containment verified. Gold labels and validator files stay outside the coding agent and JEV inputs.

Keyword and JEV arms deliver at most 8,192 UTF-8 bytes of complete serialized historical evidence, including metadata and escaping. Do not describe this as an exact token cap. Model-reported tokens remain the authoritative usage measurement. JEV sees a bounded exact candidate corpus; every prefetch and all JEV input/output usage count even when the coding agent receives none of that content. Source limits, authorization, and Quarantine remain enforced by Sediment.

Record every scheduled result, failed request, and missing usage value. Report correctness and historical constraint recovery alongside input/output/cache usage by model, model/tool/read counts, bytes, latency, and quoted-price estimates with their source/date. Local coding inference has no measured dollar cost unless actual compute metering exists; never present zero API fees as free compute. Fewer coding-model tokens alone do not establish lower total usage or spending.

An unfavorable model result completes an honestly reported experiment; it does not justify tuning and rerunning the held-out comparison. Missing credentials, live isolation, or required checks leave the affected acceptance incomplete and the PR draft. Do not close #69 automatically: this is a separate evaluation with different triggering semantics.

No production API, schema, grant, Fact, Derivation, Attribution, training-label, or database migration changes. No model SDK dependency or generic selector framework. Integration uses one isolated branch; no merge is authorized by this issue.

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