Your codebase remembers. Even when your team forgets.
Wiki Forge is a decision provenance engine. It compiles your source code, git history, and PRs into a living knowledge base — not just docs, but the why behind every engineering decision. When code changes, it detects drift and rewrites only what changed.
Why
Software engineering has 23-25% annual turnover. Each departure costs 4-8 weeks of delivery time — not because the code is lost, but because the context behind it is. Why was this module built this way? What incident prompted the retry logic? Who knows how the payment flow actually works?
Wiki Forge treats institutional memory as a compiled artifact. The code + git history is the source of truth, the LLM is the compiler, and three types of output serve three audiences:
Output
Audience
What it contains
Wiki pages
PMs, designers, new engineers
Business rules, architecture, decision context
AI context files
Claude Code, Cursor, Copilot
CLAUDE.md, AGENTS.md, llms.txt
Knowledge risk reports
Engineering managers
Bus factor per module, onboarding readiness
Manual Docs
RAG / Chatbot
Google Code Wiki
Wiki Forge
Output you own
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Version-controlled
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Works offline / air-gapped
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Decision archaeology
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Auto-updates
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Reviewable as a PR
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Cost
time
per query
freemium
per compile
Your code stays yours
With --provider local, Wiki Forge pipes prompts through your local
claude or ollama CLI. Nothing leaves your machine.
Provider
Where your code goes
gemini / claude / openai
API call to vendor
local
Stays on your machine, always
Three ways to use it
1. GitHub Action (for CI/CD)
Automatically compiles docs on every push to main:
That's it. No cloning, no config. Now open any project in Claude Code and type /wf-init.
Then in any project:
/wf-init # interview + scan → creates .doc-map.json
/wf-compile --force # compile all docs from scratch
/wf-compile # incremental — only recompile drifted docs
/wf-check # preview what drifted (read-only)
/wf-health # check human-written docs for contradictions
/wf-query "how do fees work" # ask questions, save answers as wiki pages
/wf-brief # weekly shipping brief for leadership
No API key needed — Claude Code is the LLM.
3. MCP server (for AI assistants)
Give Claude direct access to your compiled wiki. One server, reads whatever repos it's pointed at:
# Local repo (engineer with git checkout)
claude mcp add wiki-forge -- wiki-forge-mcp --repo ./docs
# Remote repo (PM, no git needed)
claude mcp add wiki-forge -- wiki-forge-mcp --github acme/platform
# Multi-repo
claude mcp add wiki-forge -- wiki-forge-mcp --repo /path/to/repo1/docs --repo /path/to/repo2/docs
Claude gets four tools:
Tool
What it does
wiki_forge_why
"Why is this file this way?" — maps source file to wiki page, returns decision context
wiki_forge_who
"Who has context?" — returns ranked contributors with ownership % and bus factor
wiki_forge_search
Search the compiled wiki by keyword — returns matching pages with excerpts
wiki_forge_status
Brain health dashboard — coverage metrics, knowledge risk, action items
No LLM calls, no database, no accounts. The MCP server reads markdown files — the compiled wiki is the product, the server is just the read layer. Works across all Claude surfaces: Claude Code, Cowork, Desktop.
Keep your docs in sync with your code. LLM-powered documentation compiler.
The npm package wiki-forge receives a total of 10 weekly downloads. As such, wiki-forge popularity was classified as not popular.
We found that wiki-forge demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.It has 1 open source maintainer collaborating on the project.