Skill Eval

Evaluate whether one skill improves the produced work. Do not award credit for headings, claimed procedure, or a report that merely looks complete.

Input

Require:

• exactly one target: <INDEX name> or subject_path: <path>;
• phase: calibrate | verify;
• one surface with adapter: codex | claude-code | cursor | opencode | cline

and an exact model name;

• evals/evals.json and a resolvable old-skill or no-skill baseline.

Hash the complete subject package with scripts/hash-skill-package.mjs. Every terminal result belongs only to that hash. If the package changes, re-run the evaluation.

Safety

Keep the subject read-only. Run file-changing tasks only in disposable copies below .skill-eval-runs/. Mock consequential boundaries such as push, PR/issue creation, payments, migrations, or production services. If a safe fixture is unavailable, return INCONCLUSIVE.

Do not edit the subject, commit, push, install globally, or contact live external systems.

Run

Read [references/run-protocol.md](references/run-protocol.md), then:

1. Validate the eval definition.
2. For every case, create separate baseline and subject workspaces.
3. Run both with the same prompt, fixture, adapter, model, permissions, and

limits. Start each in a clean session.

1. Use scripts/run-harness-eval.mjs --adapter <id> .... The adapter only

translates the common run into a harness command and parses its output.

1. Judge mechanical assertions with deterministic checks. Judge semantic

quality by a blind comparison of the two produced artifacts. Store a short evidence file for every assertion and grade.

1. In verify phase, build the result described in

[references/evidence-contract.md](references/evidence-contract.md) and run scripts/compute-eval-verdict.mjs against the current subject path.

Never compare token counts between different adapters or models. Missing token telemetry is unavailable, not guessed and not automatically inconclusive; artifact quality can still prove lift. Duration is reported but does not prove lift by itself.

Calibration

Run the pairs and propose assertions, but do not issue a terminal verdict. Reject assertions that also pass on a clearly wrong artifact. A human or a separate reviewer approves the assertion set before it is added to the draft.

Trigger check

The MVP derives the trigger requirement from the package: explicit-only skills do not require an automatic-activation check; implicit skills do. Native trigger-trace verification is not implemented yet, so an implicit skill cannot receive terminal PASS from this MVP. Record it as NOT_RUN and return INCONCLUSIVE instead of trusting a claimed trigger result. Cursor also uses explicit prompt context rather than native skill loading.

Verdict

• PASS: all assertions pass, no artifact regresses, required trigger checks

pass, and at least one artifact grade or observed token comparison is better than baseline.

• FAIL: an assertion, scope boundary, trigger check, or artifact grade fails

or regresses.

• NO_LIFT: both configurations pass but the subject adds no measured value.
• INCONCLUSIVE: baseline, current hash, safe execution, required trigger, run

trace, assertion evidence, or grade evidence is missing or inconsistent.

FAIL, NO_LIFT, and INCONCLUSIVE do not justify accepting or committing the revision.

Stop

Return one calibration artifact or one terminal verdict and stop. Evaluation does not authorize fixing, committing, or accepting the result on the human's behalf.