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Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
🔒 PR Risk Scan ResultsScanned 17 changed file(s).
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🚦 Submission status: 👀 Ready for reviewRisk tier: Why this tier
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🔍 Vally Lint Results✅ All checks passed
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The upstream README for the linked source repository routes readers to Agensi referral links for Design Taste Pro and an Agensi edition of Blind Test. That creates the same free-skill-to-paid-companion promotion path identified in the reviews of #6230 and #6231, so we can’t accept this contribution in the catalog. |
Pull Request Checklist
npm startand verified thatREADME.mdis up to date.mainbranch for this pull request.Description
Checks whether a skill, an instructions file, a prompt or an MCP server changes what the agent does. It builds a fictional target with planted problems and traps (legitimate decisions that look like mistakes), writes the answer key before any run, runs the same request with and without the customization in isolated agents, grades the outputs without knowing which arm wrote them and reports what the numbers can honestly claim.
It has two levels: a quick check by default, and the full test with calibration and normalization when the numbers go public. Useful to anyone writing skills or instructions for Copilot before they publish them. The repository includes a test of the skill with its own method.
No paid service or account needed. Source, MIT: https://github.com/arez-xd/blind-test
Type of Contribution
Additional Notes
Bundled scripts, Node 18+, no dependencies, network calls or installs:
score.mjs,refcheck.mjs,blind-labels.mjswork on local files: scoring grades against the key, checking that a rewrite kept every file and line, copying results under random labels.target-server.mjsserves the test folder on 127.0.0.1; any request other than GET or HEAD gets 405 and is logged.agents/claude.yamlandagents/openai.yamlare display metadata for agents that read them.npm run skill:validateandnpx @microsoft/vally-cli lintpass.By submitting this pull request, I confirm that my contribution abides by the Code of Conduct and will be licensed under the MIT License.
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