doc-indexer — community doc-indexer, git-workflow, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Ideal for AI Agents like Claude Code needing efficient project documentation discovery and metadata extraction from markdown files Spec-Driven Git Workflow plugin for Claude Code - Comprehensive development workflow with GitHub integration, sprint management, and brownfield migration support

bodangren bodangren
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Updated: 3/2/2026

Agent Capability Analysis

The doc-indexer skill by bodangren is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Ideal for AI Agents like Claude Code needing efficient project documentation discovery and metadata extraction from markdown files

Core Value

Empowers agents to scan and index markdown files in the `docs/` directory, extracting YAML frontmatter metadata and returning a structured map of available documentation, minimizing token usage and enhancing just-in-time context provision with GitHub integration and sprint management

Capabilities Granted for doc-indexer

Indexing project documentation for efficient discovery
Extracting YAML frontmatter metadata from markdown files
Enhancing spec-driven Git workflow with comprehensive development workflow and brownfield migration support

! Prerequisites & Limits

  • Requires access to the `docs/` directory
  • Limited to markdown files with YAML frontmatter metadata
  • Optimized for use with Claude Code and GitHub integration
Labs Demo

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Boot Container Sandbox

doc-indexer

Install doc-indexer, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
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Document Indexer Skill

Purpose

Provide just-in-time context about available project documentation without loading full file content into the context window. The doc-indexer scans all markdown files in the docs/ directory, extracts their YAML frontmatter metadata, and returns a structured map of available documentation. This enables efficient discovery of specs, plans, retrospectives, and other documentation while minimizing token usage.

When to Use

Use this skill in the following situations:

  • At the beginning of any work session to understand the current state of documentation
  • When starting work on a new issue to identify relevant specs and context
  • Before proposing changes to understand existing specifications
  • When planning a sprint to review available approved specs
  • Anytime you need an overview of project documentation without reading full files

Prerequisites

  • The project must have a docs/ directory
  • Documentation files should follow the convention of including YAML frontmatter
  • The jq tool is NOT required (script works without it)

Workflow

Step 1: Run the Documentation Scanner

Execute the helper script to scan all markdown files in the docs/ directory:

bash
1bash scripts/scan-docs.sh

This will output a human-readable summary showing each document's frontmatter metadata.

For machine-readable JSON output (useful for programmatic processing):

bash
1bash scripts/scan-docs.sh -j

Step 2: Review the Documentation Map

The scanner returns information about all markdown files found in docs/, including:

  • File path: Location of the documentation file
  • Frontmatter metadata: Key-value pairs from YAML frontmatter (title, status, type, etc.)
  • Compliance warnings: Files missing YAML frontmatter are flagged

Example human-readable output:

---
file: docs/specs/001-synthesis-flow.md
title: AgenticDev Methodology
status: approved
type: spec
---
file: docs/changes/my-feature/proposal.md
title: My Feature Proposal
status: in-review
type: proposal
[WARNING] Non-compliant file (no frontmatter): docs/README.md

Example JSON output:

json
1[ 2 { 3 "file": "docs/specs/001-synthesis-flow.md", 4 "compliant": true, 5 "frontmatter": { 6 "title": "AgenticDev Methodology", 7 "status": "approved", 8 "type": "spec" 9 } 10 }, 11 { 12 "file": "docs/README.md", 13 "compliant": false, 14 "frontmatter": null 15 } 16]

Step 3: Use the Map to Identify Relevant Documentation

Based on the documentation map, identify which specific files to read for your current task:

  • For implementation work: Look for approved specs related to your issue
  • For spec proposals: Review existing specs to understand the current state
  • For sprint planning: Identify approved specs ready for implementation
  • For learning context: Find retrospectives and design docs

Step 4: Read Specific Documentation Files

Once you've identified relevant files from the map, use the Read tool to load their full content:

bash
1# Example: Read a specific spec identified from the map 2Read docs/specs/001-synthesis-flow.md

This two-step approach (scan first, then read selectively) minimizes token usage while ensuring you have access to all necessary context.

Error Handling

No docs/ Directory

Symptom: Script reports "No such file or directory"

Solution:

  • Verify you're in the project root directory
  • Check if the project has been initialized with project-init skill
  • Create docs/ directory structure if needed

Files Missing Frontmatter

Symptom: Script outputs "[WARNING] Non-compliant file (no frontmatter): ..."

Impact: These files won't have structured metadata in the output

Solution:

  • Add YAML frontmatter to documentation files for better discoverability
  • Frontmatter should be at the top of the file between --- markers
  • Example format:
    markdown
    1--- 2title: My Document 3status: draft 4type: design 5--- 6 7# Document content starts here

Script Permission Errors

Symptom: "Permission denied" when running the script

Solution:

bash
1chmod +x scripts/scan-docs.sh

Output Interpretation Guide

Frontmatter Fields

Common frontmatter fields you'll encounter:

  • title: Human-readable document title
  • status: Document state (draft, in-review, approved, archived)
  • type: Document category (spec, proposal, design, retrospective, plan)
  • epic: Associated epic issue number
  • sprint: Sprint identifier
  • author: Document author
  • created: Creation date
  • updated: Last update date

Using JSON Output Programmatically

The JSON output mode is particularly useful when:

  • Filtering documents by specific criteria (e.g., only approved specs)
  • Counting documents by type or status
  • Building automated workflows
  • Integrating with other tools

Example using jq to filter approved specs:

bash
1bash scripts/scan-docs.sh -j | jq '.[] | select(.frontmatter.status == "approved")'

Notes

  • The scanner is non-invasive and read-only - it never modifies files
  • Large projects with many docs benefit most from this just-in-time approach
  • The script scans recursively through all subdirectories in docs/
  • Empty frontmatter sections are treated as non-compliant
  • The scan is fast and can be run frequently without performance concerns
  • Consider running this at the start of each work session to stay current with documentation changes

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is doc-indexer?

Ideal for AI Agents like Claude Code needing efficient project documentation discovery and metadata extraction from markdown files Spec-Driven Git Workflow plugin for Claude Code - Comprehensive development workflow with GitHub integration, sprint management, and brownfield migration support

How do I install doc-indexer?

Run the command: npx killer-skills add bodangren/git-workflow. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for doc-indexer?

Key use cases include: Indexing project documentation for efficient discovery, Extracting YAML frontmatter metadata from markdown files, Enhancing spec-driven Git workflow with comprehensive development workflow and brownfield migration support.

Which IDEs are compatible with doc-indexer?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for doc-indexer?

Requires access to the `docs/` directory. Limited to markdown files with YAML frontmatter metadata. Optimized for use with Claude Code and GitHub integration.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add bodangren/git-workflow. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use doc-indexer immediately in the current project.

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