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Fixture skill with promotable eval scenario metadata.
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Based on SOC occupation classification
Review changed code for behavior-preserving simplification by removing dead code, eliminating duplication, extracting shared helpers, improving names, and tightening tests. Use when a user asks for code review, refactor, clean up PR, simplify, tidy up code, review my changes, or maintainability cleanup before merge.
Check if a repository or agent-facing product surface is ready for AI coding agents. Use when you need to audit repo agent compatibility, review AGENTS.md, find missing test/build commands, evaluate docs quality, assess tool/action parity, or produce a file-evidence scorecard with specific fixes.
Use when reviewing, creating, shrinking, or refactoring AGENTS.md and directly linked instruction guidance that need scoped routing, deduplication, contradiction resolution, or progressive disclosure.
Review code architecture, code quality, dependency graphs, coupling, technical debt, modularization, ownership, and test seams. Use when refactors, restructuring, tightly coupled code, or architecture decisions need proof-backed options.
Choose validation proof for tests, CI, coverage, evals, and closeout evidence: map changed files to repo-native commands, classify pass/fail/blocked ownership, preserve trace/regression artifacts, and keep local, CI, Tessl, external-review, tracker, and runtime truth separate. Use when users ask what tests to run, why validation failed, what proof is enough, or whether command evidence supports a claim.
Defensive review of AI-agent skills, plugins, and tools using Liran Tal's security principles. Use when assessing provenance, permissions, data exposure, sandboxing, or approval boundaries before adoption.
| name | skills-sdk-scenario-quality-fixture |
| description | Fixture skill with promotable eval scenario metadata. |
This fixture exists for Skills SDK scenario-quality receipt tests.
