A comprehensive code quality analysis engine that automates AI-driven code reviews, performance scoring, and cross-platform reporting for development teams.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install fightingdao-code-quality-system
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install fightingdao-code-quality-system using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Code Quality System?
The Code Quality System is an advanced integration within the Openclaw Skills ecosystem designed to maintain high software engineering standards. It functions by systematically analyzing Git repository changes, calculating multi-dimensional quality scores, and performing deep-dive AI code reviews. By synthesizing data from both frontend and backend services, it provides a centralized view of team productivity and code health.
This skill is particularly valuable for engineering leaders and DevOps teams who require structured insights into codebase evolution. It bridges the gap between raw commits and actionable intelligence, ensuring that security, performance, and maintainability are checked automatically. Whether generating weekly reports or triggering real-time notifications, this system streamlines the technical oversight process for modern development workflows.
Code Quality System Use Cases
- Automated generation of weekly and monthly developer productivity and quality reports.
- In-depth AI-powered code auditing to identify security vulnerabilities and logic errors.
- Synchronizing historical code change metrics to a database for long-term data analytics.
- Real-time team communication via 360Teams webhooks for critical code quality alerts.
- Standardizing commit message audits and correlating code changes with project task IDs.
How Code Quality System Works
- Initialize the process by performing a git fetch across all projects to ensure the analysis includes the latest remote changes.
- Match target branches and versions based on specific time periods (weekly YYYYMMDD or monthly YYYYMM) and source branch priorities.
- Filter out irrelevant files such as lock files, dependency folders, and build artifacts using predefined exclusion patterns.
- Execute AI quality scoring based on dimensions like code complexity, maintainability, and commit granularity.
- Spawn advanced AI sub-tasks using models like Kimi-k2.5 for deep, line-by-line code review and issue identification.
- Aggregate and synchronize the structured data into the relational database, covering analyses, reviews, and issues.
- Generate and distribute HTML email reports and Teams notifications to all relevant stakeholders.
Code Quality System Setup
To get started with this skill in your environment, follow these configuration steps:
# Install the cloc tool for line counting
brew install cloc
# Navigate to your skill directory and configure the environment
cd ~/.openclaw/skills/code-quality-system
cp config.example.json config.json
# Configure your database and API endpoints in config.json
# Then run a manual analysis for the current week
node scripts/analyze-code-v2.js
# Sync the results to your central database
node scripts/sync-to-db.js
Code Quality System Data Schema & Taxonomy
The skill organizes data into a structured taxonomy within the database to support Openclaw Skills reporting features:
| Table Name | Primary Function | Key Metadata |
|---|---|---|
| code_analyses | Core analysis metadata | user_id, project_id, ai_quality_score, file_changes |
| code_reviews | Commit-level history | commit_hash, commit_message, review_result |
| code_issues | AI-identified defects | file_path, severity (P0-P2), issue_type, suggestion |
| team_statistics | Aggregate performance | total_commits, active_members, avg_quality_score |
| project_statistics | Project health metrics | total_contributors, total_commits, period_value |
Code Quality System Advanced Features
- Model Orchestration: Automatically switches to high-context models like Kimi-k2.5 (262k context) for large-scale code reviews.
- Custom Exclusion Rules: Regex-based filtering to skip non-source files during statistical calculations.
- Task correlation: Automatically extracts and maps task IDs from commit messages to link code with project management tools.
- Guardrail Enforcement: Mandatory 'at least one issue' logic to ensure every project report provides actionable feedback.
- Multi-channel Reporting: Integrated support for SMTP email summaries and signed 360Teams webhook notifications.
SKILL.md
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