Evaluate
SkillDev toolsInternal Harness instruction source for evaluate. Route through visible Harness aliases instead of invoking directly.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Evaluate skill
What this skill tells your AI
The instructions your AI receives, as published by linzhe001/harness-research in .agents/skills/evaluate/SKILL.md and read by ahel’s review.
References
Read these first:
../../../.agents/references/context-layering-policy.md../../../.agents/references/commit-checkpoint-rule.md../../../.agents/references/lesson-quality-rule.md../../../.agents/references/language-policy.md../../../.agents/references/run-artifact-contract.md../../../.agents/references/documentation-evidence-rule.md../../../.agents/references/documentation-style.md../../../.agents/references/research-supervision-patterns.md../../../.agents/references/research-supervision/experiment-and-build-canvas.md../../../.agents/references/research-supervision/ai-assisted-research-workflow.md../../../.agents/references/reviewer-independence.md../../../.agents/references/review-tracing.md./references/stage-report.md../../../iteration_log.json../../../PROJECT_STATE.json../../../docs/context/contracts.mdif it exists; legacy contract files are fallback inputs before migration../../../docs/context/experiments.mdif it exists../../../docs/context/memory.mdif it exists
When To Use
Use this skill when the user wants training or evaluation results interpreted and turned into a decision.
Required Work
- Parse the relevant run artifact bundle, logs, metrics, or checkpoint metadata.
- Analyze:
- training stability
- convergence
- overfitting
- gradient and numerical issues
- Resolve the tracked metric set from active iteration context or project state, and compare against baseline metrics and prior iterations using that protocol.
- Separate metric movement, training health, missing controls, claim support, and next-experiment implications.
- Verify
pre_eval_commitfor meaningful eval work, or recordpre_eval_commit_NOT_CHANGEDwhen the committed training source already covers eval code/configs. Do not use eval output as Conclusion Evidence without a committed eval identity. - Produce the canonical report using
./references/stage-report.md. - Write observations, phenomena, findings, hypotheses, next-experiment hints,
Experiment Queue entries, Assurance Axis gaps, and Research Wiki notes to
docs/context/experiments.md. - Promote only qualified lesson candidates to
docs/context/memory.md; write rootMEMORY.mdonly for accepted lessons when the project keeps that optional bank. - Report
NOT_RUNwhen no experiments or memory context update is needed. - Record Claim Delta Evidence when a paper claim, release claim, or claim
boundary implication changed; otherwise record
claim_delta_evidence_NOT_CHANGED. - Do not promote raw run observations directly into root
MEMORY.md. - Recommend exactly one of:
NEXT_ROUND— ordinary improvement round, stay in WF10DEBUG— fixable technical issue, stay in WF10CONTINUE— handoff to orchestrator/WF11, not continue iteratingPIVOTABORT
- If invoked from
$iterate, do not take over stage-transition ownership. - Include run artifact paths as Execution Evidence and keep unverifiable result interpretations under open questions.
- Record per-Iteration Light Conclusion Evidence for completed evaluation slices; the Campaign controller validates it before an Iteration can complete.
- Use an
experimentcommit checkpoint for completed evaluation/discovery slices before long follow-up runs or handoff. - Report a Gate ledger when
docs/context/experiments.md,docs/context/memory.md, stage reports, optional legacy mirrors,iteration_log.json, claim delta evidence, or the experiment evidence index are written. If memory-quality or workflow-state checks are not run, mark themNOT_RUNwith the reason.
Context Budget
- Load active iteration plus 5 recent summaries; reference full history by path.
- Keep the report under 1200 words unless the operator requests a deep audit.
Durable Docs Render
Codex Adaptation
- Treat natural-language requests as the canonical
$evaluateflow or the evaluation sub-step of$iterate. - Use
.agents/state/current_iteration.jsonas the active iteration context path. - Preserve the original decision vocabulary (NEXT_ROUND / DEBUG / CONTINUE / PIVOT / ABORT) and per-iteration reporting behavior, but do not assume a fixed metric family.
- Use
../../../.agents/references/language-policy.mdfor reply language and for localizing natural-language report sections; keep protocol keys and decision tokens in English.
Execution Rule
Follow the local evaluation prompt, stage-report template, and language policy rather than collapsing this into a brief metrics summary.
Durable Docs Render
temporary drafts.
Signals
- GitHub stars
- 86
- Forks
- 9
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
evaluate- Source
- github.com/linzhe001/harness-research