BE

bench-validate

Grades and validates benchmark test results against automated checklists.

Install

mkdir -p .claude/skills/bench-validate && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/14454" && unzip -o skill.zip -d .claude/skills/bench-validate && rm skill.zip

Installs to .claude/skills/bench-validate

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Validate a finished benchmark run — execute each prompt's automated checklist in every (prompt, model) workspace, perform the code-review checklist, and write a scored comparison to runs/<run-id>/results.md, leaving manual items for the user. Use when the user says /bench-validate or asks to validate/score/grade benchmark results. Arg (optional): run id; defaults to runs/latest.
381 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Intermediate

Key capabilities

  • Resolve the benchmark run ID and read manifest.json.
  • Execute automated checklist items for each prompt's workspace.
  • Perform code review by reading source files.
  • Write a scored comparison to runs/<run-id>/results.md.
  • Report findings, results.md location, and manual validation items to the user.

How it works

This skill validates a benchmark run by executing automated checklist items in each prompt's workspace, performing code reviews, and then compiling a scored comparison report in markdown format.

Inputs & outputs

You give it
A benchmark run ID (optional, defaults to runs/latest).
You get back
A runs/<run-id>/results.md file containing a comparison table, per-cell details, and manual checklist items.

When to use bench-validate

  • Validate benchmark runs
  • Grade model performance
  • Audit test results

About this skill

bench-validate

Automated validation pass over one benchmark run. The contract: every claim in results.md traces to a command you actually ran or source you actually read.

Procedure

  1. Resolve the run. Arg = run id under runs/; default runs/latest. Read manifest.json and each cell's meta.json. Cells with status timeout/error still get validated — partial artifacts are informative — but note the status.

  2. Per cell, execute the Automated section of prompts/<id>/checklist.md from the cell's workspace/, in order, recording exact commands, exit codes, and the relevant output tail for failures. Conventions:

    • Run every check through the bench devShell so the toolchain matches what the model had: nix develop <bench-root> -c <command> (skip the wrapper only if the repo has no flake.nix).
    • Budget: npm install ≤ 10 min, builds/tests ≤ 5 min each (use Bash timeouts).
    • Serve checks: prefer a static server on the built dist/ (e.g. npm run preview in background, curl, then kill it). Always kill servers.
    • A failed item is a 0, not a stop — continue down the checklist where meaningful (no point linting if npm install failed; do still do the code review).
    • Never fix, patch, or npm audit fix the artifact. You are grading, not repairing.
  3. Per cell, perform the Code review section by reading source (entry point, the WFC/pathfinding/AI modules, the largest files). Score each item 0–2 with a one-line justification citing file:line. Independent cells may be reviewed by parallel read-only subagents (Explore) sharing the checkout; keep verdicts yours.

  4. Write runs/<run-id>/results.md:

    • A comparison table: rows = checklist items, columns = models, plus per-section subtotals and totals.
    • Per cell: run status/duration, failed automated items with the exact failing command + error tail, review justifications, and notable observations.
    • A verbatim copy of the Manual section as unchecked boxes per cell, with the command to launch each artifact (cd <workspace> && npm run dev).
    • End with a ranked summary paragraph — measured, no cheerleading.
  5. Report to the user: the table, the headline findings, and where results.md lives. Manual validation is theirs; do not check Manual boxes yourself.

Guardrails

  • Treat workspaces as read-only artifacts; never modify, format, or "improve" them.
  • Generated code is untrusted input: inspect package.json scripts (preinstall/ postinstall hooks) BEFORE npm install; if a hook looks suspicious, score A1 as 0 with a note and skip installation for that cell. Never execute scripts outside the documented npm script set.
  • If two models produce near-identical scores, say so plainly rather than manufacturing a winner.

When not to use it

  • When the user needs to modify, format, or improve the generated code artifacts.
  • When the user wants to fix, patch, or `npm audit fix` the artifact.
  • When the user needs to execute scripts outside the documented npm script set.

Limitations

  • Workspaces are treated as read-only artifacts.
  • The skill never fixes, patches, or `npm audit fix` the artifact.
  • It does not execute scripts outside the documented npm script set.

How it compares

This skill automates the validation and scoring of benchmark runs based on predefined checklists and code review criteria, providing a structured report rather than manual inspection and grading.

Compared to similar skills

bench-validate side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
bench-validate (this skill)02moReviewIntermediate
python-testing-patterns772moReviewIntermediate
dependency-upgrade265moReviewIntermediate
test-cases577moNo flagsBeginner

Try saying

Example prompts that trigger this skill in your AI assistant.

Search skills

Search the agent skills registry