gh-pr-review
/gh-pr-review
Recenzuje pull requesty GitHub przez orkiestrację wielu agentów, aby dokładnie zwalidować zmiany przed scaleniem.
- Autor
- WaterplanAI ↗
- Repozytorium
- agentic-config ↗
- Licencja
- MIT
- Ostatnia zmiana repozytorium
- 23.07.2026
Ocena i bezpieczeństwo
- Pliki w paczce
- 1
- Skrypty
- 0
- Komentarze HTML
- 0
- Adresy URL w SKILL.md
- 1
Brak sygnałów. Repozytorium zmienione 23.07.2026, bez odwołań do wycofanych modeli i API.
MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.
Co robi i kiedy
Recenzuje pull requesty GitHub przez orkiestrację wielu agentów, aby dokładnie zwalidować zmiany przed scaleniem.
Oryginalny opis (EN)
Reviews GitHub PRs with multi-agent orchestration for comprehensive validation. Triggers on keywords: PR review, review PR, GitHub PR review, pull request review
Jak działa
- Inputs
- Pre-Flight
- Step 1: Fetch PR Data
- Step 2: Launch Review Agents (PARALLEL)
- Step 3: Aggregate Results
- Step 4: Generate Review Report
- Step 5: Present Results
- Safety
Podgląd SKILL.md
---
name: gh-pr-review
description: "Reviews GitHub PRs with multi-agent orchestration for comprehensive validation. Triggers on keywords: PR review, review PR, GitHub PR review, pull request review"
project-agnostic: true
allowed-tools:
- Bash
- Read
- Write
- Grep
- Glob
- Task
- WebFetch
---
# GitHub PR Review
Review the GitHub pull request with comprehensive validation using multi-agent orchestration.
## Inputs
- **PR_LINK**: $1 (GitHub PR URL, e.g., `https://github.com/owner/repo/pull/123`)
- **EXPECTED_CHANGES**: $2 (Brief description of expected changes)
- **REPORT_PATH**: $3 (Optional; defaults to `tmp/mux/{date}-{uuid}/PR-{PR_NUMBER}-{UUID}.md`)
---
## Pre-Flight
1. Extract PR number from URL: `$1`
2. Generate UUID for this review session
3. Create output directory: `tmp/mux/{date}-{uuid}/`
---
## Step 1: Fetch PR Data
Use `gh` CLI to gather PR information:
```
gh pr view <PR_NUMBER> --json title,body,author,state,baseRefName,headRefName,files,additions,deletions,commits
gh pr diff <PR_NUMBER>
gh pr view <PR_NUMBER> --json comments,reviews
gh pr checks <PR_NUMBER>
```
Store PR metadata for agent context.
---
## Step 2: Launch Review Agents (PARALLEL)
Use the **Task tool** to spawn 5 agents in parallel. Each agent writes findings to its output file.
### Agent 1: Expected Changes Validation
**Subagent type**: `general-purpose`
**Task**: Compare PR diff against expected changes: `$2`
- Identify missing expected changes
- Identify unexpected/out-of-scope changes
- Report alignment score (1-10) and gaps
- Write summary to: `{OUTPUT_DIR}/01_expected_changes.md`
### Agent 2: Security Review
**Subagent type**: `general-purpose`
**Task**: Security review of PR diff
- Check for hardcoded secrets/credentials
- Check for SQL injection, command injection, XSS vulnerabilities
- Check for insecure dependencies
- Check for permission/auth issues
- Reference OWASP Top 10
- Write summary to: `{OUTPUT_DIR}/02_security.md`
### Agent 3: Code Quality Review
**Subagent type**: `general-purpose`
**Task**: Code quality review of PR diff
- Validate against project conventions (if documented)
- RUN project-configured linters and type checkers on changed files from PR diff
- REPORT any NEW violations introduced by this PR (ignore pre-existing issues)
- REPORT any pre-commit hook failures with remediation guidance (if hooks are configured)
- Check type annotations present and correct
- Check error handling (re-raise, no silent failures)
- Check function complexity and readability
- Check naming conventions and import organization
- Write summary to: `{OUTPUT_DIR}/03_code_quality.md`
### Agent 4: Test Discovery & Execution
**Subagent type**: `general-purpose`
**Task**: Discover and run tests from PR
- Find test files in diff
- Find CLI configurations (test.json, cli.py patterns)
- Execute discovered tests with pytest
- Report pass/fail with output
- Write summary to: `{OUTPUT_DIR}/04_tests.md`
### Agent 5: Logic & Bug Risk Analysis (CRITICAL)
**Subagent type**: `general-purpose`
**Model**: `opus` (requires deep reasoning)
**Task**: Critical evaluation of logic changes and bug introduction risk
#### Logic Correctness Review
- **Intent vs Implementation**: Does the code actually achieve what it's supposed to?
- **Edge Cases**: Identify unhandled edge cases (nulls, empty collections, boundary values)
- **State Management**: Check for race conditions, stale state, improper state transitions
- **Control Flow**: Verify branching logic, loop terminations, early returns are correct
- **Data Flow**: Trace data through the change - are transformations correct?
#### Bug Introduction Risk
- **Behavioral Regressions**: Changes that might break existing functionality
- **Silent Failures**: Paths where errors could be swallowed or ignored
- **Type Coercion Issues**: Implicit conversions that might lose data or precision
- **Off-by-One Errors**: Index/range calculations
- **Null Reference Risks**: Accessing properties on potentially null/undefined values
- **Resource Leaks**: Unclosed connections, file handles, memory allocations
#### Logic Smell Detection
- **Inverted Conditions**: Logic that does the opposite of what variable names suggest
- **Dead Code Paths**: Unreachable branches introduced by the change
- **Contradictory Logic**: Conditions that can never be true together
- **Missing Validation**: Input assumptions not validated
- **Inconsistent Handling**: Similar cases handled differently without reason
#### Impact Analysis
- **Downstream Effects**: What other components rely on changed code?
- **Contract Violations**: Does the change break implicit contracts with callers?
- **Assumption Changes**: Are assumptions about data/state still valid?
#### Output Format
For each issue found:
```
[SEVERITY] - [Category]
Location: file:line
Issue: [description]
Why it's a bug: [reasoning]
Fix suggestion: [if applicable]
```
- Write summary to: `{OUTPUT_DIR}/05_logic_bugs.md`
---
## Step 3: Aggregate Results
After ALL agents complete:
1. Read all agent summaries from `{OUTPUT_DIR}/*.md`
2. Synthesize findings into consolidated report
---
## Step 4: Generate Review Report
Create report at: `$3` or `tmp/mux/{date}-{uuid}/PR-{PR_NUMBER}-{UUID}.md`
### Report Template
```markdown
# PR Review: #{PR_NUMBER}
**URL**: {PR_URL}
**Title**: {PR_TITLE}
**Author**: {AUTHOR}
**Branch**: {HEAD} -> {BASE}
**Review Session**: {UUID}
**Date**: {TIMESTAMP}
---
## Executive Summary
{Overall assessment: APPROVE / REQUEST_CHANGES / NEEDS_DISCUSSION}
### Scores
| Category | Score | Status |
|----------|-------|--------|
| Expected Changes Alignment | X/10 | {emoji} |
| Logic & Bug Risk | X/10 | {emoji} |
| Security | X/10 | {emoji} |
| Code Quality | X/10 | {emoji} |
| Tests | X/10 | {emoji} |
---
## Detailed Findings
### Expected Changes
{From Agent 1}
### Logic & Bug Risk (CRITICAL)
{From Agent 5 - This section requires careful review}
#### Logic Issues Found
{List of logic correctness problems}
#### Potential Bugs Introduced
{List of bug risks with severity and reasoning}
#### Impact Assessment
{Downstream effects and contract changes}
### Security
{From Agent 2}
### Code Quality
{From Agent 3}
### Test Results
{From Agent 4}
---
## PR Review Comments
| File | Line | Severity | Comment |
|------|------|----------|---------|
| path/file.py | 42 | ERROR | Issue description |
---
## PR Review Message
{Copy-paste ready message for GitHub PR comment}
### Recommendation
- APPROVE: Ready to merge
- REQUEST_CHANGES: Must address before merge
- COMMENT: No blocking issues
---
## Next Steps
{Actionable recommendations}
```
---
## Step 5: Present Results
Output summary to user:
```
PR REVIEW COMPLETE
PR: #{PR_NUMBER} - {TITLE}
Report: {REPORT_PATH}
Top Issues:
{Critical findings}
Proposed Actions:
1. Post review: gh pr review {PR_NUMBER} --comment --body-file {REPORT}
2. Request changes: gh pr review {PR_NUMBER} --request-changes
3. Approve: gh pr review {PR_NUMBER} --approve
Which action?
```
---
## Safety
- READ-ONLY GitHub operations (no automatic posting)
- All review comments require USER CONFIRMATION before posting
- Tests run in local environment only
- Sensitive data redacted from reports
Wersje
W bazie nie ma innych skilli o nazwie gh-pr-review.
Identyczna treść występuje jeszcze w 1 innych folderach na GitHubie. Tu pokazujemy jedną, najlepiej ocenioną kopię.
Migawka bazy z 28.10.2026 · wersja paczki cc40300e2c14 (skrót SHA-256 całej paczki)
Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.
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