quality
npx machina-cli add skill YoniChechik/claude-code-config/quality --openclawRuns quality checks and fixes in a single pass.
Process
Step 1: Slop Agent
Use Task tool with subagent_type="slop-agent" to remove AI-generated slop and fail-fast violations.
Step 2: Structure Agent
Use Task tool with subagent_type="structure-agent" to enforce top-to-bottom code organization.
Step 3: Lint Agent
Use Task tool with subagent_type="lint-agent" to format, auto-fix linting, and fix type errors.
Report results to user.
Source
git clone https://github.com/YoniChechik/claude-code-config/blob/main/skills/quality/SKILL.mdView on GitHub Overview
This skill runs quality checks and fixes in a single pass. It uses a Slop Agent to remove AI-generated slop and fail-fast violations, a Structure Agent to enforce top-to-bottom code organization, and a Lint Agent to format, auto-fix linting, and fix type errors, then reports results to the user.
How This Skill Works
Implemented as a sequence of Task tool invocations with subagent_type parameters: slop-agent, structure-agent, and lint-agent. Each agent performs its role—removing slop, enforcing structure, and applying formatting and lint fixes—before results are aggregated and reported back to the user.
When to Use It
- Before merging a pull request to ensure code quality and consistency
- During a code review to surface organization or linting issues quickly
- When refactoring or restructuring legacy code to enforce a clean layout
- In CI/CD pipelines to automatically validate formatting, style, and type errors
- After making changes that trigger style or lint violations to auto-correct them
Quick Start
- Step 1: Run Slop Agent to remove AI-generated slop and fail-fast violations
- Step 2: Run Structure Agent to enforce top-to-bottom code organization
- Step 3: Run Lint Agent to format, auto-fix linting, and fix type errors; results are reported to the user
Best Practices
- Run quality checks in a single pass to minimize drift between steps
- Start with the Slop Agent to remove noise from AI-generated content
- Follow with the Structure Agent to normalize code organization before linting
- Let the Lint Agent auto-fix formatting and type errors where safe
- Review the reported results and validate changes before deployment
Example Use Cases
- Lint and format a Python repository, fixing PEP8 and type hints
- Clean up a JavaScript/TypeScript project with ESLint and Prettier rules
- Reorganize a legacy codebase by enforcing a top-to-bottom module structure
- Integrate into CI to automatically run quality checks and report results
- Run on a generated codebase to remove AI slop and apply consistent formatting