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agent-sort

Classify repository AI configuration components into daily workflows and library references.

1|Updated Apr 6, 2026
Search Tags:#automation#workflow#optimization#configuration#cleanup#repository
One-click install
npx skills add https://github.com/vrcms/everything-qwen-code --skill agent-sort-vrcms
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-sort
Source: https://github.com/vrcms/everything-qwen-code/tree/main/.qwen/skills/agent-sort
Command: npx skills add https://github.com/vrcms/everything-qwen-code --skill agent-sort-vrcms

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the issue of configuration bloat by trimming the Everything Qwen Code (EQC) bundle to only the components actually required by the current repository.

Core Features & Use Cases

  • Evidence-Based Classification: Categorizes skills, agents, and rules into DAILY (active) or LIBRARY (reference) buckets based on actual file system evidence.
  • Automated Install Planning: Generates a tailored installation plan to ensure the AI environment remains performant and relevant.
  • Use Case: A developer working on a Go project can use this to automatically demote unused Python or Rust patterns to the library, keeping the active workspace clean and focused.

Quick Start

Run the agent-sort skill to analyze the current repository and generate a custom installation plan for your project.

Frequently Asked Questions about agent-sort

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

FAQPage Schema
How do I clean up unnecessary AI context in my repository?▼

To clean up unnecessary AI context, you can classify configuration components into active daily workflows and searchable library references using evidence-based file system analysis. This prunes unused patterns, keeping your active workspace focused and performant.

What is configuration bloat in AI development environments?▼

Configuration bloat occurs when an AI bundle contains excessive unused components. It is solved by trimming the Everything Qwen Code bundle to only the components required by the current repository, ensuring the environment remains relevant.

How do I generate a custom installation plan for my project's AI environment?▼

You generate a tailored installation plan by analyzing the current repository to categorize skills, agents, and rules into active or reference buckets. This ensures the AI environment matches your project's specific language stacks.

Does AI configuration cleanup require repository-level file system access?▼

Yes, AI configuration cleanup requires repository-level file system access. This access is necessary to verify language stacks and dependency manifests, providing the evidence needed to demote unused patterns to the library.

What's the best way to optimize a Go project's AI configuration?▼

The best way to optimize a Go project's AI configuration is to automatically demote unused Python or Rust patterns to the library. This evidence-based classification keeps the active workspace clean and focused on daily workflows.

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