dyad-multi-pr-review

name: dyad:multi-pr-review description: Multi-agent code review system that spawns three independent Claude sub-agents to review PR diffs. Each agent receives files in different randomized order to reduce ordering bias. Issues are classified as high/medium/low severity. Results are aggregated using consensus voting - only issues identified by 2+ agents where at least one rated it medium or higher severity are reported and posted as PR comments. Use when reviewing PRs, performing code review with multiple perspectives, or when consensus-based issue detection is needed.

Multi-Agent PR Review

This skill creates three independent sub-agents to review code changes, then aggregates their findings using consensus voting.

Overview

1. Fetch PR diff files
2. Spawn 3 sub-agents, each receiving files in different randomized order
3. Each agent reviews and classifies issues (high/medium/low criticality)
4. Aggregate results: report issues where 2+ agents agree on medium+ severity
5. Post findings: one summary comment + inline comments on specific lines

Workflow

Step 1: Fetch PR Diff

# Get changed files from PR
gh pr diff <PR_NUMBER> --repo <OWNER/REPO> > pr_diff.patch

# Or get list of changed files
gh pr view <PR_NUMBER> --repo <OWNER/REPO> --json files -q '.files[].path'

Step 2: Run Multi-Agent Review

Execute the orchestrator script:

python3 scripts/orchestrate_review.py \
  --pr-number <PR_NUMBER> \
  --repo <OWNER/REPO> \
  --diff-file pr_diff.patch

The orchestrator:

1. Parses the diff into individual file changes
2. Creates 3 shuffled orderings of the files
3. Spawns 3 parallel sub-agent API calls
4. Collects and aggregates results

Step 3: Review Prompt Template

Each sub-agent receives this prompt (see references/review_prompt.md):

Review these code changes for correctness issues. For each issue found:
1. Identify the file and line(s)
2. Describe the issue
3. Classify criticality: HIGH / MEDIUM / LOW

HIGH: Security vulnerabilities, data loss risks, crashes, broken core functionality
MEDIUM: Logic errors, edge cases, performance issues, maintainability concerns
LOW: Style issues, minor improvements, documentation gaps

Output JSON array of issues.

Step 4: Consensus Aggregation

Issues are matched across agents by file + approximate line range + issue type. An issue is reported only if:

• 2+ agents identified it AND
• At least one agent rated it MEDIUM or higher

Step 5: Post PR Comments

The script posts two types of comments:

1. Summary comment: Overview with issue counts by severity
2. Inline comments: Detailed feedback on specific lines of code

python3 scripts/post_comment.py \
  --pr-number <PR_NUMBER> \
  --repo <OWNER/REPO> \
  --results consensus_results.json

Options:

• --dry-run: Preview comments without posting
• --summary-only: Only post summary, skip inline comments

File Structure

scripts/
  orchestrate_review.py  - Main orchestrator, spawns sub-agents
  aggregate_results.py   - Consensus voting logic
  post_comment.py        - Posts findings to GitHub PR
references/
  review_prompt.md       - Sub-agent review prompt template
  issue_schema.md        - JSON schema for issue output

Configuration

Environment variables:

• ANTHROPIC_API_KEY - Required for sub-agent API calls
• GITHUB_TOKEN - Required for PR access and commenting

Optional tuning in orchestrate_review.py:

• NUM_AGENTS - Number of sub-agents (default: 3)
• CONSENSUS_THRESHOLD - Min agents to agree (default: 2)
• MIN_SEVERITY - Minimum severity to report (default: MEDIUM)
• THINKING_BUDGET_TOKENS - Extended thinking budget (default: 128000)
• MAX_TOKENS - Maximum output tokens (default: 128000)

Extended Thinking

This skill uses extended thinking (interleaved thinking) with max effort by default. Each sub-agent leverages Claude's extended thinking capability for deeper code analysis:

• Budget: 128,000 thinking tokens per agent for thorough reasoning
• Max output: 128,000 tokens for comprehensive issue reports

To disable extended thinking (faster but less thorough):

python3 scripts/orchestrate_review.py \
  --pr-number <PR_NUMBER> \
  --repo <OWNER/REPO> \
  --diff-file pr_diff.patch \
  --no-thinking

To customize thinking budget:

python3 scripts/orchestrate_review.py \
  --pr-number <PR_NUMBER> \
  --repo <OWNER/REPO> \
  --diff-file pr_diff.patch \
  --thinking-budget 50000