wiki-auto-documenter

Generate hierarchical Azure DevOps wiki pages from Python codebases using AST analysis and multi-agent orchestration.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/linus-mcmanamey/multi-agent-user-story-development --skill wiki-auto-documenter
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: wiki-auto-documenter
Source: https://github.com/linus-mcmanamey/multi-agent-user-story-development/tree/main/.claude/skills/wiki-auto-documenter
Command: npx skills add https://github.com/linus-mcmanamey/multi-agent-user-story-development --skill wiki-auto-documenter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, pandas, pymupdf, duckdb, loguru, rich, textual, watchdog, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the laborious process of creating and maintaining comprehensive documentation for Python codebases in Azure DevOps Wiki. It ensures documentation is always synchronized with the codebase, follows strict formatting standards, and includes crucial details like code structure, dependencies, and cross-references, saving significant manual effort and improving developer onboarding.

Core Features & Use Cases

  • Multi-Agent Orchestration: Decomposes large documentation tasks into parallel sub-tasks for efficient processing.
  • Automated Code Analysis: Uses AST to extract classes, functions, docstrings, dependencies, and infer purpose from Python files.
  • Azure DevOps Wiki Integration: Publishes hierarchical wiki pages, including directory indexes and file-specific documentation, with bidirectional links to source code.
  • Strict Markdown Formatting: Enforces consistent markdown standards for readability and maintainability across all generated documentation.
  • Use Case: After a major refactor or when onboarding new team members, use this skill to automatically generate or update the entire project's Python codebase documentation in Azure DevOps Wiki, ensuring all new code is documented and existing docs are up-to-date.

Quick Start

Explain how to use the wiki-auto-documenter skill to document the 'python_files/gold/' directory, including the expected output and execution time.

Frequently Asked Questions about wiki-auto-documenter

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

FAQPage Schema
How do I automatically generate Azure DevOps Wiki documentation from my Python codebase?

Automatically generate Azure DevOps Wiki documentation by running the wiki-auto-documenter skill against your Python repository. It analyzes code structure, extracts classes and functions, and publishes a hierarchical wiki with bidirectional links to source files, eliminating manual documentation work.

Can I document multiple Python directories at once, like gold, silver, and utilities folders?

Yes, the skill processes entire repositories and multiple directories in parallel using multi-agent orchestration. It constructs a unified hierarchical wiki structure mirroring your code layout across all specified directories simultaneously.

What happens to my existing Azure DevOps Wiki documentation when I run the auto-documenter?

The skill publishes new hierarchical wiki pages with synchronized content reflecting your current codebase. Establish a workflow to review generated pages before replacing existing documentation to avoid overwriting manual edits.

Does wiki-auto-documenter extract docstrings and dependencies from Python code?

Yes, it uses AST parsing to extract docstrings, classes, functions, and dependencies from Python files, automatically inferring code purpose and including these details in generated wiki documentation.

What Python dependencies does the wiki-auto-documenter require?

The skill requires requests, pandas, pymupdf, duckdb, loguru, rich, textual, and watchdog. Ensure these packages are installed in your environment before running the documentation generation workflow.

How does wiki-auto-documenter handle large codebases and rate limits?

It implements a three-tier multi-agent workflow with parallel processing and JSON-based data exchange. Rate-limiting and environment-based configuration manage Azure DevOps REST API calls efficiently across large repositories.