ln-312-review-findings-worker
Use when an evaluation coordinator needs normalized findings from target artifacts and research evidence.
npx skills add majiayu000/claude-skill-registry --skill ln-312-review-findings-worker --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
> **Paths:** File paths (`references/`, `../ln-*`) are relative to this skill directory. **Type:** L3 Worker **Category:** 3XX Planning # Review Findings Worker ## Mandatory Read **MANDATORY READ:** Load `references/evaluation_worker_runtime_contract.md`, `references/evaluation_summary_contract.md` **MANDATORY READ:** Load `../ln-310-multi-agent-validator/references/phase2_research_audit.md`, `../ln-310-multi-agent-validator/references/penalty_points.md` **MANDATORY READ:** Load `../ln-310-multi-agent-validator/references/premortem_validation.md`, `../ln-310-multi-agent-validator/references/cross_reference_validation.md` ## Purpose - analyze the target artifact or diff - convert evidence into normalized findings - for `mode=story`: calculate penalty points across 30 criteria per `phase2_research_audit.md` - for `mode=plan_review`: evaluate criteria #5, #6, #21, #28 only (no penalty accumulation) - avoid narrative-only review output ## Mode Gate - `mode=story`: full pipeline — pre-mortem, cross-reference, penalty points across 30 criteria, build fix plan - `mode=plan_review`: applicability check, stack detection, evaluate criteria #5 (standards), #6 (library versions), #21 (alternat
- Mandatory Read
- Purpose
- Mode Gate
- Runtime
- Workflow
- Phase 0: Config
- Phase 1: Load Target
- Phase 2: Pre-mortem (mode=story)
- Phase 3: Cross-Reference (mode=story)
- Phase 4: Criteria Audit
- Phase 5: Penalty Calculation (mode=story)
- Phase 6: Normalize Findings
- Phase 7: Write Summary
- Phase 8: Self-Check
What does the ln-312-review-findings-worker skill do?
Use when an evaluation coordinator needs normalized findings from target artifacts and research evidence.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ln-312-review-findings-worker --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.