ln-312-review-findings-worker
Use when an evaluation coordinator needs normalized findings from target artifacts and research evidence.
How do I install this agent skill?
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-312-review-findings-workerIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill is an evaluation worker designed to audit and normalize findings from project artifacts, such as User Stories and technical plans, against industry standards. It uses a local Node.js-based runtime to manage audit states and checkpoints entirely within the local file system. No security vulnerabilities or malicious patterns were detected.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · 1 issue
What does this agent skill do?
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 perphase2_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 planmode=plan_review: applicability check, stack detection, evaluate criteria #5 (standards), #6 (library versions), #21 (alternatives), #28 (library features) only, normalize findings without penalty accumulation
Runtime
Runtime family:
evaluation-worker-runtime
Required manifest fields:
identifierphase_ordersummary_kind=review-findingsoperation=findings
Recommended phase_order:
PHASE_0_CONFIGPHASE_1_LOAD_TARGETPHASE_2_PREMORTEM(mode=story, complexity >= Medium)PHASE_3_CROSS_REFERENCE(mode=story, multi-story Epic)PHASE_4_CRITERIA_AUDITPHASE_5_PENALTY_CALCULATION(mode=story only)PHASE_6_NORMALIZE_FINDINGSPHASE_7_WRITE_SUMMARYPHASE_8_SELF_CHECK
Workflow
Phase 0: Config
Load runtime manifest, target identifiers, and any linked research artifact paths.
Phase 1: Load Target
Load only the target artifacts needed for the review scope.
Phase 2: Pre-mortem (mode=story)
Execute pre-mortem analysis per premortem_validation.md:
- Skip for trivial Stories (1-2 tasks, no external deps, known tech).
- Execute for Stories with complexity >= Medium (3+ tasks, external deps, or unfamiliar tech).
- Tigers (evidence-based risks) feed Risk criterion #20 — add to risk table BEFORE penalty calc.
- Elephants (unstated assumptions) feed Assumptions criterion #24 — add with
[pre-mortem]tag, Confidence=LOW. - Paper Tigers (fears without evidence) — document and dismiss.
- Include pre-mortem table in audit report.
Phase 3: Cross-Reference (mode=story)
Execute cross-reference analysis per cross_reference_validation.md:
- Skip if Epic has only 1 Story or all siblings Done/Canceled.
- Load sibling Stories via
list_issues(project=Epic.id). - Check AC overlap (#25): structured traceability first, keyword fallback advisory-only.
- Check task duplication (#26): structured match primary.
- Include cross-reference findings in audit report.
Phase 4: Criteria Audit
mode=story: evaluate all 30 criteria against Story/Tasks perphase2_research_audit.mdAuto-Fix Actions Reference.mode=plan_review: evaluate criteria #5, #6, #21, #28 only (standards + solution groups).- Cross-check claims against provided research evidence when present.
Phase 5: Penalty Calculation (mode=story)
- Assign penalty points per violation using severity levels from
phase2_research_audit.md(CRITICAL=10, HIGH=5, MEDIUM=3, LOW=1). - Apply multiple-violation rules per
penalty_points.mdCalculation Rules. - Calculate total penalty points.
- Build fix plan for each violation.
- Format penalty audit table per
penalty_points.mdReport Format.
Phase 6: Normalize Findings
Each finding should prefer structured fields such as:
idseveritycategorysubjectevidencerecommendation
Phase 7: Write Summary
Emit summary_kind=review-findings.
Payload must include:
worker=ln-312statusoperation=findingswarnings
Prefer these fields when available:
findingsmetrics.penalty_total(mode=story)metrics.criteria_violated(list of criterion numbers)metrics.fix_plan(array of {criterion, action, severity})metrics.premortem_summary(when executed)metrics.cross_reference_summary(when executed)
Phase 8: Self-Check
- Remove duplicates.
- Remove unsupported claims.
- Verify penalty calculation matches
penalty_points.mdrules (mode=story). - Record
pass=trueonly after summary write.
Definition of Done
- Target artifact loaded
- Pre-mortem executed or justified as skipped (mode=story)
- Cross-reference executed or justified as skipped (mode=story)
- Criteria audit completed (30 for story, #5/#6/#21/#28 for others)
- Penalty points calculated and fix plan built (mode=story)
- Findings normalized
- Unsupported claims removed
-
review-findingssummary written - Self-check passed
Version: 1.0.0 Last Updated: 2026-04-10
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/levnikolaevich/claude-code-skills/ln-312-review-findings-worker">View ln-312-review-findings-worker on skillZs</a>