Review me
Multi-angle adversarial review of any artifact (spec, plan, ADR, or implementation). Use when the user wants a review, approval check, sign-off, or readiness assessment.From its SKILL.md
npx -y skills add ShinewineW/lucideye --skill review-meAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
1.4 KB, 253 tokens by cl100k_base, as published. Nobody here has run it
Review this artifact from multiple adversarial angles of your choosing — pick the lenses that matter most for THIS document.
SPEC mode: interrogate goals, boundaries, trade-offs, missing decisions. IMPL mode: interrogate mutations, migrations, error paths, observability.
Each angle must surface at least one finding — "no issues" means you haven't looked hard enough. When multiple angles flag the same issue, promote its severity. Do not ask questions; derive from context.
End with:
- Findings by angle, tagged [BLOCKER / CONCERN / NOTE]
- Clash — where angles disagree
- Verdict: approve | approve-with-conditions | request-changes | reject-for-now
- If approving: the single biggest risk you're accepting.
Enhanced Review
For high-stakes artifacts or reviews that warrant additional scrutiny:
- Read
references/dual-review.mdand apply independent dual review, a both-pass verdict gate, fresh-reviewer fix cycles, and bounded batch sampling where appropriate. - Read
references/review-orchestration.mdand classify findings through RECONCILE, stop after a bounded review loop, and offer the documented cross-model escalation protocol when appropriate.
What ships with it: 3 files
18.8 KB alongside SKILL.md
agents/
- openai.yaml237 B
references/
- dual-review.md12.7 KB
- review-orchestration.md5.9 KB