review
SolidFull qualitative review of the agent setup. Reads every file, applies per-component rubrics, runs 21 cross-type optimization checks, and produces KEEP/REVIEW/REMOVE verdicts. Use when the user wants a deep review, redundancy check, or quality assessment of their setup.
Install
Quality Score: 82/100
Skill Content
Details
- Author
- redhat-community-ai-tools
- Repository
- redhat-community-ai-tools/harness-eval
- Created
- 3 months ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- Apache-2.0
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
lint
Run deterministic static analysis on the full agent setup (CLAUDE.md, skills, commands, hooks, agents, MCP configs). 108 rules + system-level analysis (token budget, trigger overlaps, dependencies). No LLM. Use when the user wants a fast lint check, CI gate, or structural health report.
reviewing-agent-instructions
Use when the user wants to review AI-agent instruction files (CLAUDE.md, skills, drift-log, hooks) for pollution, duplication, dead references, contradictions, or architectural debt. Manual on-demand only. Outputs a committed markdown report; does no auto-fix. Always run together with /claude-md-improver for full coverage.
qa-reviewer
Runs a structured multi-phase verification pass on completed AI agent work — catching bugs, missed requirements, and incorrect assumptions before changes are committed. Triggers on: "check your work", "review this", after complex multi-step implementations, before committing major refactors, or proactively after any task longer than five steps.