bodangren/doc-indexer

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 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 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:

[
  {
    "file": "docs/specs/001-synthesis-flow.md",
    "compliant": true,
    "frontmatter": {
      "title": "AgenticDev Methodology",
      "status": "approved",
      "type": "spec"
    }
  },
  {
    "file": "docs/README.md",
    "compliant": false,
    "frontmatter": null
  }
]

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:

# Example: Read a specific spec identified from the map
Read 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:

  ---
  title: My Document
  status: draft
  type: design
  ---
  
  # Document content starts here
  

Script Permission Errors

Symptom: "Permission denied" when running the script

Solution:

chmod +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 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