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Revue de code multi-réviseurs

/team-review

Organisez une révision de code parallèle impliquant plusieurs réviseurs, chacun se concentrant sur un aspect spécifique de la qualité. Cela permet de générer un rapport consolidé et dédupliqué,

wshobsonwshobson
★41.7k
5 juin 2026
MIT
// contenu du skill

description: "Launch a multi-reviewer parallel code review with specialized review dimensions"

argument-hint: "<target> [--reviewers security,performance,architecture,testing,accessibility] [--base-branch main]"


Team Review

Orchestrate a multi-reviewer parallel code review where each reviewer focuses on a specific quality dimension. Produces a consolidated, deduplicated report organized by severity.

Pre-flight Checks

  1. Verify CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set
  2. Parse $ARGUMENTS:
  • <target>: file path, directory, git diff range (e.g., main...HEAD), or PR number (e.g., #123)
  • --reviewers: comma-separated dimensions (default: security,performance,architecture)
  • --base-branch: base branch for diff comparison (default: main)

Phase 1: Target Resolution

  1. Determine target type:
  • File/Directory: Use as-is for review scope
  • Git diff range: Use Bash to run git diff {range} --name-only to get changed files
  • PR number: Use Bash to run gh pr diff {number} --name-only to get changed files
  1. Collect the full diff content for distribution to reviewers
  2. Display review scope to user: "{N} files to review across {M} dimensions"

Phase 2: Team Spawn

  1. Use TeamCreate tool to create the team with team_name: "review-{timestamp}" and description
  2. For each requested dimension, use Agent tool to spawn a teammate:
  • name: {dimension}-reviewer (e.g., "security-reviewer")
  • subagent_type: "agent-teams:team-reviewer"
  • prompt: Include the dimension assignment, target files, and diff content
  1. Use TaskCreate for each reviewer's task:
  • Subject: "Review {target} for {dimension} issues"
  • Description: Include file list, diff content, and dimension-specific checklist

Phase 3: Monitor and Collect

  1. Wait for all review tasks to complete (check TaskList periodically)
  2. As each reviewer completes, collect their structured findings
  3. Track progress: "{completed}/{total} reviews complete"

Phase 4: Consolidation

  1. Deduplicate: Merge findings that reference the same file:line location
  2. Resolve conflicts: If reviewers disagree on severity, use the higher rating
  3. Organize by severity: Group findings as Critical, High, Medium, Low
  4. Cross-reference: Note findings that appear in multiple dimensions

Phase 5: Report and Cleanup

  1. Present consolidated report:
   ## Code Review Report: {target}

   Reviewed by: {dimensions}
   Files reviewed: {count}

   ### Critical ({count})
   [findings...]

   ### High ({count})
   [findings...]

   ### Medium ({count})
   [findings...]

   ### Low ({count})
   [findings...]

   ### Summary
   Total findings: {count} (Critical: N, High: N, Medium: N, Low: N)
  1. Send shutdown_request to all reviewers
  2. Call TeamDelete to remove team resources
// source originale publique
wshobson/agents
/plugins/agent-teams/commands/team-review.md
Licence : MIT
Projet indépendant, non affilié à Anthropic. Ce skill reste la propriété de son auteur original.
// installer ce skill
Collez cette commande dans votre terminal à la racine de votre projet :
mkdir -p .claude/commands && curl -o ".claude/commands/team-review.md" "https://raw.githubusercontent.com/wshobson/agents/main/plugins/agent-teams/commands/team-review.md"
Ensuite dans Claude Code, tapez /team-review pour l'activer.
open_in_newVoir la source originale
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// informations
Créateurwshobson
Étoiles★ 41.7k
LicenceMIT
Mis à jour5 juin 2026
Format.md
AccèsGratuit
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