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/index-knowledge

@cb1203a
by Titomynameistito/skills1 stars
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Generate a hierarchical AGENTS.md knowledge base for any codebase. Analyzes project structure, scoring directories by complexity and domain distinctness, then produces root and subdirectory AGENTS.md files concise enough for LLM context windows. Triggers on requests to "index", "document", "map", or "generate knowledge" for a codebase, or when onboarding onto a new project.

Use this Skill: https://skilld.dev/gh/mynameistito/skills/index-knowledge

Nothing lands on disk. Nothing to clean up.

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Edit a local copy. It keeps the author and licence.

README.md

≈626 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Index Knowledge

Generate a hierarchical AGENTS.md knowledge base for any codebase. Produces concise, machine-readable orientation docs scored by complexity and domain distinctness. Fully OS-agnostic — works on macOS, Linux, WSL, Windows PowerShell, and Windows CMD.

Platform Support

This skill uses agent-native tools (glob, grep, read) for all structural analysis instead of platform-specific shell commands. No bash or PowerShell required — the same workflow runs identically on every platform.

Structure

  • SKILL.md - Skill definition with frontmatter metadata and full workflow instructions
  • metadata.json - Document metadata (version, organization, abstract)

What It Does

  1. Discovery - Scans project structure in parallel using explore agents + agent-native tools (glob, grep, read) + LSP symbols
  2. Scoring - Rates each directory by file count, symbol density, module boundaries, and export centrality
  3. Generation - Produces root + subdirectory AGENTS.md files, each under 150 lines
  4. Review - Deduplicates, trims, and validates output against quality gates

Usage

# Default: update mode (modify existing + create new where warranted)
index-knowledge

# Regenerate from scratch
index-knowledge --create-new

# Limit directory depth
index-knowledge --max-depth=2

Scoring Criteria

Factor Weight High Threshold
File count 3x >20
Subdir count 2x >5
Code ratio 2x >70%
Unique patterns 1x Has own config
Module boundary 2x Has index.ts/init.py
Symbol density 2x >30 symbols
Export count 2x >10 exports
Reference centrality 3x >20 refs

AGENTS.md Output Format

Root files get the full treatment: OVERVIEW, STRUCTURE, WHERE TO LOOK, CODE MAP, CONVENTIONS, ANTI-PATTERNS, COMMANDS, NOTES.

Subdirectory files are leaner: OVERVIEW, WHERE TO LOOK, CONVENTIONS, ANTI-PATTERNS — never repeating parent content.

All files target 50-150 lines. No generic advice. No obvious info. Telegraphic style.

Contributing

When modifying the skill:

  1. Edit SKILL.md for workflow changes
  2. Update metadata.json version for releases
  3. Keep instructions parallel-first (multiple Task calls in one message)
  4. Never add generic content — everything should be project-specific
  5. Use agent-native tools (glob, grep, read) for all structural analysis — do not assume bash or PowerShell availability

Source: SKILL.md on GitHub

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skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

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No alerts1mo3 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    The skill is a hierarchical documentation generator that analyzes codebases to create concise AGENTS.md orientation files. It leverages platform-native tools and subprocess execution for efficiency. The skill is authored by a trusted developer and adheres to security best practices, including directory exclusion and OS-agnostic execution logic. No malicious patterns were identified.

  • Socket1mo

    No alerts

  • Snyk4mo

    Risk: LOW · No issues

Signed by skilld at cb1203a. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 weeks ago.

Activeupdated last month
metadata
{
  "author": "mynameistito, dmmulroy",
  "version": "1.1.0"
}

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