🌊 Deep Wiki

AI-Powered Wiki Generator for Code Repositories — Ported for Pi Coding Agent

Generate comprehensive, structured, Mermaid-rich documentation wikis for any codebase — 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 — catalogue + all pages + onboarding guides + VitePress site | | /skill:deep-wiki crisp | Fast wiki generation — concise, parallelized, rate-limit-friendly. 5–8 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 lookup <question> | Look up answers in wiki first, update if needed | | /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 — evidence-first |

Quick Start

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

# Fast wiki — 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?

# Look up answers in wiki first
/skill:deep-wiki lookup How does authentication work?

# 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 → Scan → Catalogue (JSON TOC) → Per-Section Pages → Assembled Wiki
                                                    ↓
                                         Mermaid Diagrams + Citations
                                                    ↓
                                         Onboarding Guides (Contributor, Staff Engineer, Executive, PM)
                                                    ↓
                                         VitePress Site (Dark Theme + Click-to-Zoom)
                                                    ↓
                                         AGENTS.md Files (Only If Missing)
                                                    ↓
                                         llms.txt + llms-full.txt (LLM-friendly)
                                                    ↓
                                         GitHub Pages Deployment (Optional)

| Step | Component | What It Does | |------|-----------|-------------| | 1 | wiki-architect | Analyzes repo → hierarchical JSON table of contents | | 2 | wiki-page-writer | For each TOC entry → 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 → 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 — no hand-waving
4. Diagram-rich: Minimum 3–5 dark-mode Mermaid diagrams per page using multiple diagram types, with click-to-zoom and <!-- Sources: ... --> comment blocks. More diagrams = better — 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 → Subsystems → Components → Methods
9. Never invent: All content derived from actual code — 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

Style Modifiers

Deep Wiki supports two special style modifiers that can be added to any command to adjust the tone, depth, and target audience of the generated documentation.

ELI-PhD (Explain Like I Have a PhD)

When the user includes ELI-PhD or explain like I have a PhD in their query, the documentation is crafted for readers with PhD-level technical reasoning but who are unfamiliar with the specific domain.

Approach:

• Analogy-first, formalism-second: Use structural analogies before formal definitions
• Concept hierarchy mapping: Explicitly state prerequisites, new concepts, and deferred topics
• "What problem does this solve?" framing: Start with failure modes of naive approaches
• Minimum viable mental model: Reconstruct the smallest derivable concept set
• Two-level explanation: Shape summary → precise details
• Historical/motivational narrative: Explain why the field converged on this approach
• Worked examples before definitions: Concrete examples before abstract definitions

Usage:

/skill:deep-wiki generate ELI-PhD
/skill:deep-wiki research "caching strategy" ELI-PhD
/skill:deep-wiki page "Authentication Flow" ELI-PhD

ELIPC (Explain Like I'm a Potential Client)

When the user includes ELIPC or explain like I'm a potential client in their query, the documentation is crafted for busy, skeptical technical decision-makers (evaluators, potential clients).

Approach:

• Lead with the villain (pain point), not the solution: Each page opens with specific pain points
• "So what" ladder: Drill down to business impact
• Movie trailer structure: Stakes → result → explanation
• Name the enemy: "Unlike X, this doesn't require Y"
• One-sentence positioning: "For [who], this is the [what] that [does X], unlike [alternative]"
• Social proof: Put impressive numbers in headlines
• Before/after demo: Show painful before vs. clean after
• Reduce activation energy: One-line install, live playground, Colab

Usage:

/skill:deep-wiki crisp ELIPC
/skill:deep-wiki ask "Why use this framework?" ELIPC
/skill:deep-wiki lookup "authentication benefits" ELIPC

Supported Commands

Style modifiers are supported in the following commands:

• generate
• crisp
• page
• research
• ask
• lookup

They cannot be used with catalogue, changelog, onboard, agents, llms, ado, build, or deploy as those commands produce different output types not affected by style variations.

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 — agents check here first via file reading | llms-full.txt | wiki/llms-full.txt | Full inlined docs — agents load this for comprehensive context | AGENTS.md | Root + key folders | Standard agent instructions file — references wiki docs in Documentation section | Wiki pages | wiki/**/*.md | Searchable via file search — 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 → gets project summary + links to all wiki pages
2. Agent reads specific wiki pages → gets full documentation with source citations
3. Agent searches for patterns → finds relevant wiki sections across the repository
4. Agent reads AGENTS.md → Documentation section points to wiki and onboarding guides

Plugin Structure

deep-wiki/
├── agents/
│   ├── wiki-architect.md
│   ├── wiki-writer.md
│   └── wiki-researcher.md
├── commands/
│   ├── generate.md
│   ├── crisp.md
│   ├── catalogue.md
│   ├── page.md
│   ├── changelog.md
│   ├── research.md
│   ├── ask.md
│   ├── onboard.md
│   ├── agents.md
│   ├── llms.md
│   ├── ado.md
│   ├── build.md
│   └── deploy.md
└── README.md

License

MIT