@amb007/deep-wiki

AI-powered wiki generator for code repositories - Pi Coding Agent skill

Package details

skill

Install @amb007/deep-wiki from npm and Pi will load the resources declared by the package manifest.

$ pi install npm:@amb007/deep-wiki
Package
@amb007/deep-wiki
Version
1.0.0
Published
Apr 26, 2026
Downloads
68/mo ยท 68/wk
Author
amb007
License
MIT
Types
skill
Size
121.3 KB
Dependencies
0 dependencies ยท 0 peers
Pi manifest JSON
{
  "skills": [
    "SKILL.md"
  ]
}

Security note

Pi packages can execute code and influence agent behavior. Review the source before installing third-party packages.

README

๐ŸŒŠ Deep Wiki

AI-Powered Wiki Generator for Code Repositories โ€” Ported for Pi Coding Agent

Generate comprehensive, structured, Mermaid-rich documentation wikis for any codebase โ€” with dark-mode VitePress sites, onboarding guides, and deep research capabilities. Distilled from the prompt architectures of OpenDeepWiki and deepwiki-open.

Installation

See INSTALL.md for installation instructions.

Commands

Command Description
/skill:deep-wiki generate Generate a complete wiki โ€” catalogue + all pages + onboarding guides + VitePress site
/skill:deep-wiki crisp Fast wiki generation โ€” concise, parallelized, rate-limit-friendly. 5โ€“8 pages, no build step
/skill:deep-wiki catalogue Generate only the hierarchical wiki structure as JSON
/skill:deep-wiki page <topic> Generate a single wiki page with dark-mode Mermaid diagrams
/skill:deep-wiki changelog Generate a structured changelog from git commits
/skill:deep-wiki research <topic> Multi-turn deep investigation with evidence-based analysis
/skill:deep-wiki ask <question> Ask a question about the repository
/skill:deep-wiki onboard Generate 4 audience-tailored onboarding guides (Contributor, Staff Engineer, Executive, PM)
/skill:deep-wiki agents Generate AGENTS.md files for pertinent folders (only where missing)
/skill:deep-wiki llms Generate llms.txt and llms-full.txt for LLM-friendly project access
/skill:deep-wiki ado Generate a Node.js script to convert wiki to Azure DevOps Wiki-compatible format
/skill:deep-wiki build Package generated wiki as a VitePress site with dark theme
/skill:deep-wiki deploy Generate GitHub Actions workflow to deploy wiki to GitHub Pages

Agents

Agent Description
wiki-architect Analyzes repos, generates structured catalogues + onboarding architecture
wiki-writer Generates pages with dark-mode Mermaid diagrams and deep citations
wiki-researcher Deep research with zero tolerance for shallow analysis โ€” evidence-first

Quick Start

# Generate a full wiki with onboarding guides and VitePress site
/skill:deep-wiki generate

# Fast wiki โ€” concise, parallelized, avoids rate limits
/skill:deep-wiki crisp

# Just the structure
/skill:deep-wiki catalogue

# Single page with dark-mode diagrams
/skill:deep-wiki page Authentication System

# Generate onboarding guides
/skill:deep-wiki onboard

# Build VitePress dark-theme site
/skill:deep-wiki build

# Research a topic (evidence-based, 5 iterations)
/skill:deep-wiki research How does the caching layer work?

# Ask a question
/skill:deep-wiki ask What database migrations exist?

# Generate llms.txt for LLM-friendly access
/skill:deep-wiki llms

# Deploy wiki to GitHub Pages (optional)
/skill:deep-wiki deploy

How It Works

Repository โ†’ Scan โ†’ Catalogue (JSON TOC) โ†’ Per-Section Pages โ†’ Assembled Wiki
                                                    โ†“
                                         Mermaid Diagrams + Citations
                                                    โ†“
                                         Onboarding Guides (Contributor, Staff Engineer, Executive, PM)
                                                    โ†“
                                         VitePress Site (Dark Theme + Click-to-Zoom)
                                                    โ†“
                                         AGENTS.md Files (Only If Missing)
                                                    โ†“
                                         llms.txt + llms-full.txt (LLM-friendly)
                                                    โ†“
                                         GitHub Pages Deployment (Optional)
Step Component What It Does
1 wiki-architect Analyzes repo โ†’ hierarchical JSON table of contents
2 wiki-page-writer For each TOC entry โ†’ rich Markdown with dark-mode Mermaid + citations
3 wiki-onboarding Generates 4 audience-tailored onboarding guides in onboarding/ folder
4 wiki-vitepress Packages all pages into a VitePress dark-theme static site
5 wiki-changelog Git commits โ†’ categorized changelog
6 wiki-researcher Multi-turn investigation with evidence standard
7 wiki-qa Q&A grounded in actual source code
8 wiki-agents-md Generates AGENTS.md files for pertinent folders (only if missing)
9 wiki-llms-txt Generates llms.txt + llms-full.txt for LLM-friendly access
10 wiki-ado-convert Converts VitePress wiki to Azure DevOps Wiki-compatible format

Design Principles

  1. Source-linked citations: Before any task, resolve the source repo URL (or confirm local). All citations use [file:line](REPO_URL/blob/BRANCH/file#Lline) for remote repos, (file:line) for local
  2. Structure-first: Always generate a TOC/catalogue before page content
  3. Evidence-based: Every claim cites file_path:line_number with clickable links โ€” no hand-waving
  4. Diagram-rich: Minimum 3โ€“5 dark-mode Mermaid diagrams per page using multiple diagram types, with click-to-zoom and <!-- Sources: ... --> comment blocks. More diagrams = better โ€” use them liberally for architecture, flows, state, data models, and decisions.
  5. Table-driven: Prefer tables over prose for any structured information. Use summary tables, comparison tables, and always include a "Source" column with citations.
  6. Progressive disclosure: Big picture first, then drill into details. Every section starts with a TL;DR.
  7. Hierarchical depth: Max 4 levels for component-level granularity
  8. Systems thinking: Architecture โ†’ Subsystems โ†’ Components โ†’ Methods
  9. Never invent: All content derived from actual code โ€” trace real implementations
  10. Dark-mode native: All output designed for dark-theme rendering (VitePress)
  11. Depth before breadth: Trace actual code paths, never guess from file names
  12. Agent-discoverable: Output placed at standard paths (llms.txt at repo root, AGENTS.md in key folders) so coding agents and MCP tools find documentation automatically

Agent & MCP Integration

The generated output is designed to be discoverable by coding agents using the Pi Coding Agent framework:

File Path Discovery Method
llms.txt Repo root (./llms.txt) Standard llms.txt spec location โ€” agents check here first via file reading
llms-full.txt wiki/llms-full.txt Full inlined docs โ€” agents load this for comprehensive context
AGENTS.md Root + key folders Standard agent instructions file โ€” references wiki docs in Documentation section
Wiki pages wiki/**/*.md Searchable via file search โ€” all pages contain source-linked citations
llms.txt wiki/.vitepress/public/ Served at /llms.txt on deployed VitePress site

How it works with Pi Coding Agent:

  1. Agent reads llms.txt โ†’ gets project summary + links to all wiki pages
  2. Agent reads specific wiki pages โ†’ gets full documentation with source citations
  3. Agent searches for patterns โ†’ finds relevant wiki sections across the repository
  4. Agent reads AGENTS.md โ†’ Documentation section points to wiki and onboarding guides

Plugin Structure

deep-wiki/
โ”œโ”€โ”€ agents/
โ”‚   โ”œโ”€โ”€ wiki-architect.md
โ”‚   โ”œโ”€โ”€ wiki-writer.md
โ”‚   โ””โ”€โ”€ wiki-researcher.md
โ”œโ”€โ”€ commands/
โ”‚   โ”œโ”€โ”€ generate.md
โ”‚   โ”œโ”€โ”€ crisp.md
โ”‚   โ”œโ”€โ”€ catalogue.md
โ”‚   โ”œโ”€โ”€ page.md
โ”‚   โ”œโ”€โ”€ changelog.md
โ”‚   โ”œโ”€โ”€ research.md
โ”‚   โ”œโ”€โ”€ ask.md
โ”‚   โ”œโ”€โ”€ onboard.md
โ”‚   โ”œโ”€โ”€ agents.md
โ”‚   โ”œโ”€โ”€ llms.md
โ”‚   โ”œโ”€โ”€ ado.md
โ”‚   โ”œโ”€โ”€ build.md
โ”‚   โ””โ”€โ”€ deploy.md
โ””โ”€โ”€ README.md

License

MIT