ac-qa-reviewer
Quality assurance review for implementations. Use when reviewing code quality, checking implementation standards, performing QA cycles, or validating feature quality.
Best use case
ac-qa-reviewer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Quality assurance review for implementations. Use when reviewing code quality, checking implementation standards, performing QA cycles, or validating feature quality.
Teams using ac-qa-reviewer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ac-qa-reviewer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ac-qa-reviewer Compares
| Feature / Agent | ac-qa-reviewer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Quality assurance review for implementations. Use when reviewing code quality, checking implementation standards, performing QA cycles, or validating feature quality.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
Cursor vs Codex for AI Workflows
Compare Cursor and Codex for AI coding workflows, repository assistance, debugging, refactoring, and reusable developer skills.
SKILL.md Source
# AC QA Reviewer
Perform quality assurance reviews on feature implementations.
## Purpose
Reviews completed features for code quality, adherence to standards, security issues, and best practices before marking features as complete.
## Quick Start
```python
from scripts.qa_reviewer import QAReviewer
reviewer = QAReviewer(project_dir)
result = await reviewer.review_feature("auth-001")
```
## Review Dimensions
### Code Quality
- Clean code principles
- DRY (Don't Repeat Yourself)
- SOLID principles
- Code complexity metrics
### Security
- Input validation
- SQL injection prevention
- XSS prevention
- Secure authentication
### Performance
- Algorithm efficiency
- Database query optimization
- Memory usage
- Caching opportunities
### Testing
- Test coverage
- Test quality
- Edge case coverage
- Integration tests
### Documentation
- Code comments
- API documentation
- README updates
- Type annotations
## Review Result
```json
{
"feature_id": "auth-001",
"approved": true,
"score": 85,
"dimensions": {
"code_quality": {"score": 90, "issues": []},
"security": {"score": 85, "issues": ["Consider rate limiting"]},
"performance": {"score": 80, "issues": []},
"testing": {"score": 88, "issues": []},
"documentation": {"score": 82, "issues": ["Add docstring to validate_token"]}
},
"blocking_issues": [],
"suggestions": [
"Consider extracting authentication middleware",
"Add rate limiting for login endpoint"
],
"auto_fixable": ["missing_docstring"]
}
```
## QA Workflow
```
1. SCAN → Static analysis of changed files
2. ANALYZE → Check against quality rules
3. SECURITY → Security-specific checks
4. REVIEW → Contextual code review
5. REPORT → Generate review report
6. FIX → Auto-fix simple issues (optional)
7. APPROVE → Mark as QA passed or request changes
```
## Quality Gates
```yaml
gates:
minimum_score: 70
blocking_categories:
- security_critical
- test_failures
required_checks:
- linting_passes
- type_checks_pass
- tests_pass
- coverage_minimum
```
## Auto-Fix Capabilities
The reviewer can automatically fix:
- Missing type hints
- Formatting issues
- Simple code style violations
- Missing docstrings (basic)
## Integration
- Input: Completed features from `ac-task-executor`
- Uses: `ac-code-validator` for static analysis
- Reports to: `ac-state-tracker`
## API Reference
See `scripts/qa_reviewer.py` for full implementation.Related Skills
act-code-reviewer
Review JusticeHub code against ACT ecosystem values. Enforces cultural protocols, ALMA principles, and regenerative design.
academic-reviewer
Expert guidance for reviewing academic manuscripts submitted to journals, particularly in political science, economics, and quantitative social sciences. Use when asked to review, critique, or provide feedback on academic papers, research designs, or empirical strategies. Emphasizes methodological rigor, causal identification strategies, and constructive feedback on research design.
grail-miner
This skill assists in setting up, managing, and optimizing Grail miners on Bittensor Subnet 81, handling tasks like environment configuration, R2 storage, model checkpoint management, and performance tuning.
lets-go-rss
A lightweight, full-platform RSS subscription manager that aggregates content from YouTube, Vimeo, Behance, Twitter/X, and Chinese platforms like Bilibili, Weibo, and Douyin, featuring deduplication and AI smart classification.
chrome-debug
This skill empowers AI agents to debug web applications and inspect browser behavior using the Chrome DevTools Protocol (CDP), offering both collaborative (headful) and automated (headless) modes.
whisper-transcribe
Transcribes audio and video files to text using OpenAI's Whisper CLI, enhanced with contextual grounding from local markdown files for improved accuracy.
vly-money
Generate crypto payment links for supported tokens and networks, manage access to X402 payment-protected content, and provide direct access to the vly.money wallet interface.
ontopo
An AI agent skill to search for Israeli restaurants, check table availability, view menus, and retrieve booking links via the Ontopo platform, acting as an unofficial interface to its data.
astro
This skill provides essential Astro framework patterns, focusing on server-side rendering (SSR), static site generation (SSG), middleware, and TypeScript best practices. It helps AI agents implement secure authentication, manage API routes, and debug rendering behaviors within Astro projects.
modal-deployment
Run Python code in the cloud with serverless containers, GPUs, and autoscaling using Modal. This skill enables agents to generate code for deploying ML models, running batch jobs, serving APIs, and scaling compute-intensive workloads.
ux
This AI agent skill provides comprehensive guidance for creating professional and insightful User Experience (UX) designs, covering user research, information architecture, interaction design, visual guidance, and usability evaluation. It aims to produce actionable, user-centered solutions that avoid generic AI aesthetics.
thor-skills
An entry point and router for AI agents to manage various THOR-related cybersecurity tasks, including running scans, analyzing logs, troubleshooting, and maintenance.