benchmark-validator

name	benchmark-validator
description	Benchmark validation procedure for one assigned benchmark-related target. For optimization EXP-* targets, independently classify candidate outcome. For engineering VAL-* or legacy engineering targets, prove or disprove the required benchmark/performance assertion.

Benchmark Validator

Use this skill for a validation assignment targeting exactly one benchmark-related assertion.

For optimization EXP-* targets, you are not selecting the winner or optimizing further. You independently decide whether the experiment produced a trustworthy outcome under its contract.

For optimization EXP-* targets, act as an adversarial tester for the selected candidate. The contract is the minimum bar, not the whole test plan. Before promotion, define and run a compact but comprehensive validation plan that attacks the candidate's likely correctness and performance failure modes.

For engineering VAL-* or legacy engineering targets, do not use optimization outcome semantics. Pass only when the assigned benchmark, performance, correctness, and guardrail behavior required by the assignment and contract is proven with fresh evidence.

Inputs

Read:

• Validation assignment.
• The single assigned benchmark-related contract.
• AGENTS.md.
• Experiment ledger path cited by the assignment or contract.
• Candidate artifact/ref/patch/checksum cited by the assignment, contract, or ledger.
• Measurement protocol, correctness/guardrail commands, protected files, and source/baseline refs cited by the contract.
• For optimization targets, also inspect visible runtime resources read-only when useful: changed files, benchmark scripts, fixtures, public outputs, baseline/reference artifacts, verifier-adjacent code, logs, and generated artifacts. Do not mutate these resources, copy protected artifacts into a submission, or make submitted code depend on evaluator-only locations.

If the assignment targets more than one benchmark-related assertion, fail the assignment as too broad and request attention.

Procedure

1. Identify artifacts

   • Parent/baseline ref.
   • Candidate ref or patch artifact.
   • Benchmark command, run count, aggregation, variance policy.
   • Correctness and guardrail commands.
   • Protected benchmark/scoring/data/verifier files.

2. Audit evidence integrity

   • Inspect candidate changes affecting benchmark scripts, scoring, data, fixtures, golden outputs, correctness verifiers, generated expected outputs, seeds, or measurement config.
   • If proof is weakened or unapproved metric surfaces changed, classify an optimization experiment invalid; for an engineering target, mark the item passed=false.

3. Define adversarial validation plan

   • For optimization EXP-*, do this before remeasurement. Do not only run the contract's benchmark command.
   • From the contract, ledger, changed files, source, available fixtures, benchmark scripts, baseline/reference artifacts, public outputs, and visible runtime resources, identify the correctness and performance risk axes this candidate could break.
   • Build a compact test plan that includes the contract-required checks plus targeted/adversarial/proxy cases for changed surfaces. Cover important input, data, media, config, size, timing, cache, concurrency, edge, stress, and failure-mode axes when they are relevant to the candidate.
   • For each case, state the expected correctness evidence, the failure boundary, and whether timing evidence is needed. Record limitations for risk axes that cannot be tested in the validation environment.
   • If the contract or ledger does not provide enough oracle, candidate binding, or correctness information to build a meaningful adversarial plan, classify the optimization experiment invalid rather than promoting from aggregate speed alone.

4. Remeasure independently

   • Reconstruct parent and candidate states using the method assigned by the assignment or contract.
   • Avoid destructive operations on the shared workspace.
   • Run parent and candidate under the declared protocol.
   • Capture raw outputs, aggregate values, spread/noise, environment, and deviations.

5. Run correctness and guardrails

   • Required correctness/quality/compatibility/safety checks must run before objective metric comparison can promote a candidate.
   • For optimization EXP-*, run the adversarial validation plan as well as the contract-required checks.

For optimization EXP-* targets, use passed=true for promoted, rejected, or legitimate budget_exhausted; use passed=false for invalid.

For engineering VAL-* or legacy engineering targets, use normal validation semantics: passed=true only when the assigned benchmark/performance assertion and required guardrails pass with fresh evidence. A rejected candidate, failed guardrail, missing evidence, or budget-exhausted result is passed=false unless the contract explicitly defines that outcome as the required behavior.

7. Write regression ledger only for invalid
   • If passed=false, write <regressions_dir>/<item_id>.md with setup, command, expected credible measurement or required behavior, observed invalidating issue, and evidence artifact paths.

Report

## Experiment
- Item ID: <id>
- Parent artifact: <ref/path>
- Candidate artifact: <ref/path>
- Ledger: <path>

## Evidence Integrity
- Changed protected/evidence-sensitive paths: <list>
- Verdict: <credible | invalid>

## Measurements
- Parent: <runs, aggregate, spread, raw paths>
- Candidate: <runs, aggregate, spread, raw paths>
- Improvement: <calculation and threshold>

## Adversarial Validation Plan
- Risk axes: <candidate-specific axes attacked>
- Cases: <case -> expected evidence -> failure boundary>
- Limitations: <untested risk axes and why>

## Correctness And Guardrails
- `<command>` -> exit <code>, 
 Per-case adversarial results:  passed/rejected/invalid evidence>


 
 Reason: 


 

Call end_node with exactly one item for the assigned target id, then exit immediately.