ai-wiki 0.1.3

Structured knowledge wiki CLI for AI agents

AI Wiki — Structured Knowledge Encyclopedia

A CLI-based knowledge wiki system that stores, searches, and manages knowledge learned by AI assistants as structured YAML data.

한국어 README

Security Notice: AI Wiki has no authentication or authorization. It is designed for local use only. Do not expose the CLI, web UI, or data directory to external networks. All data is stored unencrypted on the local filesystem.

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Why AI Wiki?

AI coding agents (Claude Code, Gemini CLI, GPT Codex) have no built-in way to retain and reuse knowledge across sessions or projects — every conversation starts from scratch. AI Wiki is a structured knowledge store that agents read and write directly. Save a piece of knowledge once, and every agent in every project can access it automatically — no copy-paste, no repeated research.

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Features

• Structured YAML Storage — Accumulate knowledge as key-value structured data, not markdown prose
• FTS5 Full-Text Search — SQLite FTS5-based keyword search for Korean and English
• Vector Semantic Search — sentence-transformers + sqlite-vec embedding search
• Hybrid Search (RRF Fusion) — Combines FTS5 + vector search via RRF (Reciprocal Rank Fusion): score = Σ 1/(k+rank_i)
• Quality Gates — 5-level automatic evaluation of confidence, sources, and verification
• Auto Cross-Reference — Automatic detection and bidirectional linking of related documents
• Git Auto-Commit — Automatic Git history recording on every document change
• AI Agent Skill Integration — Auto-generates skill files for Claude Code (~/.claude/skills/), Gemini CLI (~/.gemini/skills/), and GPT Codex (~/.codex/skills/)
• Wiki Name Customization — Name entered during init is displayed in the web UI header
• Token Optimization — Efficient operation with large document sets via DB metadata queries

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Installation

User Installation (pip)

Requires Python 3.11+

pip install ai-wiki
ai-wiki init ~/my-wiki

Developer Installation (source)

git clone https://github.com/j-dev-team/ai-wiki.git
cd ai-wiki
python -m venv .venv
source .venv/bin/activate   # Linux/macOS
# .venv\Scripts\activate    # Windows
pip install -e ".[test]"

Windows Note: Use python instead of python3.

Interactive Init Flow

ai-wiki init runs interactively:

1. Language Selection — English / 한국어
2. Wiki Name — Displayed in the web UI header (saved in .ai-wiki.yaml)
3. Agent Selection — Choose which AI agents you use (default: Claude Code)
4. Preset Selection — Category structure matching your wiki's purpose

Agent Selection UI:

Which AI agents do you use? (comma-separated numbers)
  1. Claude Code
  2. Gemini CLI
  3. GPT Codex
Select [1,2,3] (default: 1):

• Default: 1 (Claude Code only)
• Multiple: 1,2 → Claude Code + Gemini CLI
• All: 1,2,3
• Skills are installed only to the selected agent paths (saved in .ai-wiki.yaml)

Preset	Description
general	General knowledge (default)
tech	Technology & development focused
business	Business & management focused
research	Research & academic focused

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Quick Start

# Search documents (hybrid: FTS5 + vector auto-combined)
ai-wiki search "python"

# List documents (recent first, default 50)
ai-wiki list

# Filter by category + sort by title
ai-wiki list --category technology/python --sort title

# Pagination
ai-wiki list --limit 20 --offset 40

# Get a document
ai-wiki get <document-id>

# Create a document
ai-wiki create \
  --title "Python Basics" \
  --category "technology/programming" \
  --tags "python,programming" \
  --confidence 0.9 \
  --source "https://docs.python.org" \
  --content-stdin << EOF
type: knowledge
what: Python is a general-purpose interpreted programming language
creator: Guido van Rossum
release_year: 1991
paradigm:
  - object-oriented
  - functional
  - procedural
use_cases:
  - web development
  - data science
  - automation
  - AI/ML
EOF

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How It Works

1. You ask your AI agent a question
2. The agent automatically searches the wiki via skill trigger
3. If found   -> agent uses the knowledge to answer
4. If not found -> agent researches, then saves new knowledge to the wiki
5. Next time any agent asks the same question -> instant answer from wiki

Your Question
     |
     v
+-----------+   skill   +---------+   search   +------------------+
| AI Agent  | --------> | ai-wiki | ---------> | AI Wiki          |
|           |           |  (CLI)  |            | (YAML + DB)      |
+-----------+           +---------+            +------------------+
     ^                      |                        |
     |         hit          |<-- found --------------+
     |                      |
     |         miss         v
     |              +--------------+
     +-- answer <-- |   Research   |
          + save    | (web / docs) |
                    +--------------+

All projects and all agents share the same wiki — knowledge accumulates automatically over time.

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Web UI

# Start web UI
ai-wiki-web

# Default port: 5000 → http://localhost:5000
# Wiki name is read from the `name` field in .ai-wiki.yaml

See the security notice at the top of this document.

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CLI Command Reference

Basic CRUD

Command	Description
ai-wiki init [path]	Initialize a new wiki (directory structure + config)
ai-wiki create	Create a new document
ai-wiki get <ID>	Get a document by ID
ai-wiki update <ID>	Update an existing document
ai-wiki delete <ID> --confirm	Delete a document
ai-wiki list	List all documents (--sort, --category, --limit, --offset)
ai-wiki destroy [path]	Destroy a wiki (remove skill files, env vars, directory)
ai-wiki upgrade-skill	Upgrade skill files to the latest version

Search

Command	Description
ai-wiki search "query"	Hybrid search (FTS5 + vector, auto-combined via RRF)
ai-wiki vsearch "query"	Semantic vector search
ai-wiki similar <ID>	Find documents similar to a given document
ai-wiki tag <tag>	List documents with a specific tag
ai-wiki tags	List all tags and document counts

Quality Management

Command	Description
ai-wiki quality <ID>	Single document quality report
ai-wiki quality-all	Batch quality check for all documents
ai-wiki verify <ID>	Update document verification date
ai-wiki verify <ID> --human	Mark as human-verified
ai-wiki verify-queue	List documents needing verification
ai-wiki review <ID>	Generate verification checklist

Wiki Maintenance

Command	Description
ai-wiki reindex	Rebuild search index
ai-wiki vindex	Rebuild vector index
ai-wiki lint	Wiki health check
ai-wiki lint --fix	Health check + auto-fix
ai-wiki maintain	Run lint + quality + todo together
ai-wiki backlinks <ID>	List documents referencing this document
ai-wiki sync-backlinks	Bulk sync all bidirectional backlinks

Analysis & Exploration

Command	Description
ai-wiki stats	Access statistics (Top N views/searches)
ai-wiki gaps	Gap analysis by category
ai-wiki todo	Auto-collected task list for the wiki
ai-wiki stale	List outdated documents (default: 90 days)
ai-wiki discover	Find isolated, low-quality, or stale documents
ai-wiki path <ID1> <ID2>	Shortest path between two documents (BFS)
ai-wiki cluster	Document topic clustering
ai-wiki history <ID>	Git change history for a document

Export / Import

Command	Description
ai-wiki export <ID>	Export as Markdown or YAML
ai-wiki export-all	Batch export all documents
ai-wiki ingest <file>	Ingest a source file (auto-creates stub document)

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Hybrid Search

ai-wiki search automatically combines FTS5 keyword search and vector semantic search.

• RRF (Reciprocal Rank Fusion) algorithm merges both result sets
• Returns a unified hybrid_score field
• Vector search (sentence-transformers, sqlite-vec) is included in the default installation — no extra setup needed

# Hybrid search (default)
ai-wiki search "machine learning python"

# Pure vector search only
ai-wiki vsearch "machine learning python"

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Document Structure (YAML Schema)

id: tech-python-abc123
title: Python Basics
category: technology/programming
tags:
  - python
  - programming
confidence: 0.9
version: 1
created_at: 2026-01-01T00:00:00Z
last_modified: 2026-01-01T00:00:00Z
last_verified: 2026-01-01T00:00:00Z
sources:
  - https://docs.python.org
related:
  - tech-django-xyz789
author: claude
content:
  type: knowledge
  what: Python is a general-purpose interpreted programming language
  creator: Guido van Rossum
  release_year:
    value: 1991
    _v:
      level: verified       # unverified | sourced | verified | corroborated | human_verified | disputed
      source: https://docs.python.org
  use_cases:
    - web development
    - data science
  _meta:
    maturity: mature        # stub | draft | review | mature
    completeness: 0.85
  _changelog:
    - date: 2026-01-01T00:00:00Z
      action: created
      fields: [what, creator]
      note: Document created

File Storage Path

articles/<category>/<subcategory>/<slug>.yaml

Example: articles/technology/programming/python-abc123.yaml

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Quality System

Verification Levels (_v)

Track reliability by attaching _v metadata to factual data such as numbers, dates, and quotes.

Level	Weight	Description
unverified	0.0	Not verified
sourced	0.3	Has a source
verified	0.8	Verified
corroborated	0.8	Cross-verified
disputed	0.2	Disputed
human_verified	1.0	Verified by a human

Maturity Stages

Stage	Description
stub	Minimal info, needs enrichment
draft	Basic info present
review	Under review
mature	Complete document

Quality Score Calculation

score = structure keys (15%) + word count (20%) + sources (10%) +
        tags (5%) + related docs (10%) + confidence (10%) + verification rate (30%)

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Directory Structure

Wiki Directory (after ai-wiki init)

my-wiki/
+-- articles/           # Document YAML files (subdirectories by category)
+-- data/
|   +-- wiki.db         # Search index (SQLite FTS5)
|   +-- vectors.db      # Vector embedding index
+-- sources/            # Ingested source files
+-- logs/               # Operation logs
+-- .ai-wiki.yaml       # Wiki configuration

Source Code (for developers)

src/ai_wiki/
+-- cli.py              # CLI entry point
+-- models.py           # Article data model
+-- storage.py          # File/DB storage layer
+-- index.py            # SQLite search index
+-- vector.py           # Vector search engine
+-- quality.py          # Quality validation engine
+-- schemas.py          # Type-specific schemas
+-- catalog.py          # Catalog builder
+-- wikilog.py          # Operation logger
+-- web.py              # Web UI (Flask)

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Wiki Operations

Single Wiki (Default)

Install one wiki and all AI agent projects on the system can automatically access it.

ai-wiki init ~/my-wiki

→ See AI Agent Skill Integration for details.

~/.claude/skills/my-wiki/   <- Claude Code
~/.gemini/skills/my-wiki/   <- Gemini CLI
~/.codex/skills/my-wiki/    <- GPT Codex

Project A --+
Project B --+-- Share a single wiki
Project C --+

Multi Wiki

Run multiple independent wikis on a single system.

Creating Wiki Instances

# Work wiki
ai-wiki init ~/work-wiki
# -> Wiki name: "Work Wiki"
# -> Preset: business

# Personal knowledge wiki
ai-wiki init ~/knowledge-wiki
# -> Wiki name: "My Knowledge"
# -> Preset: general

Switching Wikis

Switch the target wiki using the AI_WIKI_ROOT environment variable.

# Search work wiki
AI_WIKI_ROOT=~/work-wiki ai-wiki search "client"

# Search personal wiki
AI_WIKI_ROOT=~/knowledge-wiki ai-wiki search "python"

Agent Skill Integration

ai-wiki init auto-generates skill files for each selected agent, one per wiki.

~/.claude/skills/
  +-- work-wiki/SKILL.md        (AI_WIKI_ROOT=~/work-wiki)
  +-- knowledge-wiki/SKILL.md   (AI_WIKI_ROOT=~/knowledge-wiki)

~/.gemini/skills/  ...  ~/.codex/skills/  (same pattern)

Project A --+
Project B --+-- Access both wiki skills
Project C --+

→ See AI Agent Skill Integration for full details.

• Data: Fully isolated per wiki (separate articles/, data/)
• Program: Single shared ai-wiki CLI
• Skills: Independent skill files per wiki, accessible from all projects

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Environment Variables

Variable	Description
AI_WIKI_ROOT	Wiki root directory path (required)

Automatically registered during ai-wiki init.

# Manual setup (Windows)
setx AI_WIKI_ROOT "C:\Users\you\my-wiki"

# Manual setup (Linux/macOS)
export AI_WIKI_ROOT="$HOME/my-wiki"

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Development / Testing

# Activate virtual environment
source .venv/bin/activate   # Linux/macOS
.venv\Scripts\activate      # Windows

# Run tests
pytest

# Reinstall package (after source changes)
pip install -e .

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Dependencies

Package	Purpose
click	CLI framework
pyyaml	YAML parsing/serialization
flask	Web UI server
sqlite-vec	Vector embedding search
sentence-transformers	Multilingual embedding model
pecab (optional)	Korean morphological analysis

All dependencies including vector search are installed automatically via pip install ai-wiki.

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AI Agent Skill Integration

Skill files are auto-generated during ai-wiki init. When an agent receives a knowledge-related question, the skill auto-triggers and uses the ai-wiki CLI to search, query, and create documents.

Agent	Skill Path
Claude Code	~/.claude/skills/<wiki-name>/
Gemini CLI	~/.gemini/skills/<wiki-name>/
GPT Codex	~/.codex/skills/<wiki-name>/

Skills are installed only to the agents you select during init.

• ai-wiki init — Creates skill files in the selected agent paths
• ai-wiki upgrade-skill — Updates skill files to the latest version (reads agents from .ai-wiki.yaml)
• ai-wiki destroy — Removes skill files from selected agent paths
• If agents field is missing, defaults to ["claude"] (backward compatible)

# Upgrade skill files to latest version
ai-wiki upgrade-skill

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License

MIT License. See LICENSE for details.