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ln-311-agent-reviewer

npx machina-cli add skill levnikolaevich/claude-code-skills/ln-311-agent-reviewer --openclaw
Files (1)
SKILL.md
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Paths: File paths (shared/, references/, ../ln-*) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root.

Agent Reviewer (Story)

Runs parallel external agent reviews on validated Story and Tasks, critically verifies suggestions, returns editorial improvements.

Purpose & Scope

  • Worker in ln-310 validation pipeline (invoked in Phase 5)
  • Run codex-review + gemini-review as background tasks in parallel
  • Process results as they arrive (first-finished agent processed immediately)
  • Critically verify each suggestion; debate with agent if Claude disagrees
  • Return filtered, deduplicated, verified suggestions for Story/Tasks improvement
  • Health check + prompt execution in single invocation

When to Use

  • Invoked by ln-310-story-validator Phase 5 (Agent Review)
  • After Phase 4 auto-fixes applied, Penalty Points = 0
  • Story and Tasks are in their final form before approval

Parameters

ParameterValue
review_typestoryreview
skill_group311
prompt_templateshared/agents/prompt_templates/story_review.md
verdict_acceptableSTORY_ACCEPTABLE

Inputs (from parent skill)

  • storyId: Linear Story identifier (e.g., "PROJ-123")

Workflow

MANDATORY READ: Load shared/references/agent_review_workflow.md for Health Check, Ensure .agent-review/, Load Review Memory, Run Agents, Critical Verification + Debate, Aggregate + Return, Save Review Summary, Fallback Rules, Critical Rules, and Definition of Done. Load shared/references/agent_delegation_pattern.md for Reference Passing Pattern, Review Persistence Pattern, Agent Timeout Policy, and Debate Protocol.

Unique Steps (before shared workflow)

  1. Health check: per shared workflow, filter by skill_group = 311.

  2. Get references: Call Linear MCP get_issue(storyId) -> extract URL + identifier. Call list_issues(filter: {parent: {id: storyId}}) -> extract child Task URLs/identifiers.

    • If project stores tasks locally (e.g., docs/tasks/) -> use local file paths instead of Linear URLs.
  3. Ensure .agent-review/: per shared workflow.

  4. Build prompt: Read template shared/agents/prompt_templates/story_review.md.

    • Replace {story_ref} with - Linear: {url} or - File: {path}
    • Replace {task_refs} with bullet list: - {identifier}: {url_or_path} per task
    • Save to .agent-review/{identifier}_storyreview_prompt.md (single shared file -- both agents read the same prompt)

Shared Workflow Steps

5-8) Load Review Memory, Run agents, Critical Verification + Debate, Aggregate + Return: per shared workflow.

  • {review_type} = "Story/Tasks" (for challenge template)
  1. Save Review Summary: per shared workflow "Step: Save Review Summary".

Output Format

verdict: STORY_ACCEPTABLE | SUGGESTIONS | SKIPPED
suggestions:
  - area: "security | performance | architecture | feasibility | best_practices | risk_analysis"
    issue: "What is wrong or could be improved"
    suggestion: "Specific change to Story or Tasks"
    confidence: 95
    impact_percent: 15
    source: "codex-review"
    resolution: "accepted | accepted_after_debate | accepted_after_followup | rejected"

Agent stats and debate log per shared workflow output schema.

Fallback Rules

Per shared workflow, plus:

ConditionAction
Parent skill (ln-310)Falls back to Self-Review (native Claude)

Verdict Escalation

  • No escalation. Suggestions are editorial only -- they modify Story/Tasks text.
  • Parent skill (ln-310) Gate verdict remains unchanged by agent suggestions.

Critical Rules (additional)

  • MANDATORY INVOCATION: Parent skills MUST invoke this skill. Returns SKIPPED gracefully if agents unavailable. Parent must NOT pre-check and skip.

Reference Files

  • Shared workflow: shared/references/agent_review_workflow.md
  • Agent delegation pattern: shared/references/agent_delegation_pattern.md
  • Prompt template (review): shared/agents/prompt_templates/story_review.md
  • Challenge schema: shared/agents/schemas/challenge_review_schema.json

Version: 2.0.0 Last Updated: 2026-02-11

Source

git clone https://github.com/levnikolaevich/claude-code-skills/blob/master/ln-311-agent-reviewer/SKILL.mdView on GitHub

Overview

Agent Reviewer runs Codex and Gemini reviews in parallel on validated Stories and Tasks. It processes results as they arrive, performs critical verification with debate, and returns filtered, deduplicated suggestions to improve Story/Tasks before approval.

How This Skill Works

The skill performs a health check filtered by skill_group 311, locates references via Linear MCP, ensures the .agent-review directory, and builds a single shared prompt from the Story Review template. It then runs Codex and Gemini in parallel, aggregates the first finished results, executes critical verification and debate, deduplicates the suggestions, and saves a Review Summary for governance and traceability.

When to Use It

  • During Phase 5 of the ln-310 story validation process for agent review.
  • After Phase 4 auto-fixes are applied and Penalty Points are 0.
  • When Story and Tasks are in their final form before approval.
  • When you need parallel Codex and Gemini reviews for a Story or its Tasks.
  • When you require critical verification with debate and deduped editorial suggestions.

Quick Start

  1. Step 1: Ensure the repository contains shared/references and the story_review.md template at shared/agents/prompt_templates/story_review.md.
  2. Step 2: Trigger ln-311-agent-reviewer as part of Phase 5 in the ln-310 workflow.
  3. Step 3: Inspect the verdict and apply the returned suggestions to the Story/Tasks; review the generated Review Summary.

Best Practices

  • Run in the Phase 5 window of ln-310 to align with validation timelines.
  • Ensure health check filters by skill_group 311 before execution.
  • Use the shared template at shared/agents/prompt_templates/story_review.md to build prompts.
  • Deduplicate and filter results to avoid duplicate suggestions.
  • Review the saved Review Summary and the final verdict before publishing.

Example Use Cases

  • Example: A Story PROJ-123 receives Codex and Gemini feedback, which are debated and refined into a concise set of improvements.
  • Example: Task T-45 changes are validated with parallel agent reviews and integrated into the Story via editorial suggestions.
  • Example: Conflicting recommendations are resolved through a structured debate, producing a single cohesive improvement plan.
  • Example: Acceptance criteria are tightened based on editorial feedback from both agents.
  • Example: If the parent skill ln-310 triggers a fallback, the system uses Self-Review as the default.

Frequently Asked Questions

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