repo-maintainer

Audits and reorganizes messy repositories into clean, LLM-friendly structures. It uses a non-destructive "Migration Manifest" process to safely consolidate scripts, establish documentation, and create AI context zones.

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Install skill "repo-maintainer" with this command: npx skills add auldsyababua/instructor-workflow/auldsyababua-instructor-workflow-repo-maintainer

Repository Maintainer

Overview

This skill turns disorganized codebases ("polluted roots," "orphan scripts") into structured, readable repositories. It prioritizes LLM-Readability (creating explicit context maps) and Safety (using a reversible migration manifest).

Use this skill when:

  • A repository has too many files in the root directory.
  • Documentation is missing, outdated, or scattered.
  • An LLM struggles to find relevant context due to noise.
  • You need to "refactor" the file structure without breaking git history.

Workflow

1. The Audit (Discovery)

First, analyze the repository to understand "Hot" (frequently changed) vs "Cold" (stale) zones.

  • Run scripts/scaffold_manifest.py to generate a draft manifest.
  • Identify the "blood flow" (dependencies): Does main.py import that messy script?
  • Output: A mental model of the current chaos.

2. The Manifest (Planning)

Do not move files immediately. Create a migration_manifest.yaml that defines the desired state.

  • Run scripts/scaffold_manifest.py to generate a draft manifest if you haven't already.
  • Categorize files into:
    • Core: Application logic (src/)
    • Scaffolding: Configs (.env, docker-compose)
    • Artifacts: One-off scripts (Move to archive/)
    • Knowledge: Docs (Move to docs/)
  • Review the YAML file. It is the "Contract of Changes."

3. Execution (Safe Move)

Apply the changes using the manifest.

  • Run scripts/apply_migration.py.
  • Safety Rule: This script uses git mv to preserve history.
  • Quarantine: Unknown scripts go to archive/quarantine/ rather than being deleted.

4. LLM Optimization (Contextualizing)

Once files are moved, establish the .ai/ directory.

  • Copy assets/CONTEXT_TEMPLATE.md to .ai/CONTEXT.md.
  • Fill it with a high-level summary of the architecture.
  • This ensures future agents understand why the code exists, not just what it does.

Directory Structure Standards

When planning the migration, aim for this specific structure (The "LLM-First" Architecture):

/ (Root)
├── .ai/                 # Context specifically for LLMs
│   ├── CONTEXT.md       # Architecture & Business Logic
│   └── GUIDELINES.md    # Coding standards
├── src/                 # Source code
├── scripts/             # DevOps/Maintenance scripts
├── docs/                # Human documentation
├── archive/             # Deprecated/Quarantine
└── README.md            # The Map

Source Transparency

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