afc:clean

Automate pipeline artifact cleanup, dead code scanning, and AI memory management.

7|Updated Feb 19, 2026
One-click install
npx skills add https://github.com/jhlee0409/all-for-claudecode --skill afc-clean
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: afc:clean
Source: https://github.com/jhlee0409/all-for-claudecode/tree/main/skills/clean
Command: npx skills add https://github.com/jhlee0409/all-for-claudecode --skill afc-clean

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the cleanup of artifacts generated during a development pipeline, ensuring a clean codebase and efficient memory management.

Core Features & Use Cases

  • Artifact Cleanup: Removes temporary files and directories created by the pipeline.
  • Dead Code Scan: Identifies and helps remove unused code.
  • Memory Management: Persists relevant learnings and prunes old memory entries.
  • Use Case: After a feature has been fully implemented and reviewed, use this Skill to tidy up the project, remove any leftover pipeline-specific files, and ensure the AI's memory is up-to-date and efficient.

Quick Start

Run the clean phase of the pipeline for the current feature.

Frequently Asked Questions about afc:clean

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate pipeline artifact cleanup after feature implementation?▼

Automate pipeline artifact cleanup by running bash scripts that remove temporary pipeline files and directories. This ensures a clean codebase and efficient memory management after feature implementation and review.

What is dead code scanning and how does it improve code hygiene?▼

Dead code scanning identifies unused code segments within a project to help remove them. This improves code hygiene by ensuring the codebase remains clean and maintainable during pipeline cleanup.

How do I prune old memory entries in an automated development workflow?▼

Prune old memory entries by running the cleanup phase of the pipeline, which persists relevant learnings while removing outdated entries. This maintains an efficient knowledge base for AI memory.

Do I need bash scripts to manage pipeline state and delete artifacts?▼

Yes, you need bash scripts to manage pipeline state and delete artifacts. The cleanup process requires executing these scripts to remove temporary files and manage memory effectively.

When should I run a codebase cleanup in an automated development pipeline?▼

Run a codebase cleanup during the post-implementation phase after a feature is fully implemented and reviewed. This ensures temporary pipeline files are removed and the AI memory is updated.