AI-oriented documentation toolkit.
Project description
AI Docs Toolkit
AI Docs Toolkit is a documentation toolkit for AI-assisted software development.
It treats documentation as an engineering interface between humans, AI agents, code, tests and change management. The project is post-MVP and is hardening planning, validation, distribution and integration workflows.
Purpose
The toolkit is intended for projects where:
- AI agents participate in implementation;
- system knowledge must stay readable for humans and usable by automation;
- documentation should define constraints, expected behavior and validation rules;
- changes should be traceable across business rules, architecture, contracts, modules, acceptance criteria and code.
The core idea is that documentation should not be a secondary artifact created after implementation. It should guide implementation, validation and review.
Current Status
The published beta package includes:
- schema and structure validation for Markdown documents with YAML front matter;
- document graph output;
- impact analysis;
- context bundle output;
- an executable
ai-docsCLI; - optional local MCP runtime entrypoint.
Installation
Install the published beta package:
python -m pip install ai-docs-toolkit==0.1.0b10
ai-docs --version
For ephemeral execution with uvx:
uvx --from ai-docs-toolkit==0.1.0b10 ai-docs --version
For the optional local MCP runtime:
python -m pip install "ai-docs-toolkit[mcp]==0.1.0b10"
ai-docs-mcp --project-root .
After a stable release exists, package install commands can omit the beta version pin.
Quick Start
Bootstrap a repository for AI Docs Toolkit:
ai-docs init
ai-docs validate
For a documentation-only bootstrap without AGENTS.md:
ai-docs init --profile minimal
The command creates missing toolkit files and skips existing files by default.
Use --force only when you explicitly want to overwrite toolkit-owned target files.
Validate a configured project:
ai-docs validate
Generate machine-readable validation output:
ai-docs validate --json
Build a document graph:
ai-docs graph --format json
Analyze impact for changed files:
ai-docs impact --changed
Prepare an agent context bundle for changed files:
ai-docs context --changed
Repository Bootstrap
Repository bootstrap is an explicit command. Package installation does not modify project files.
Default agent-oriented bootstrap:
ai-docs init
Minimal bootstrap:
ai-docs init --profile minimal
The source repository may be private or unavailable to agents in consuming projects. Package usage does not require access to repository-local documentation files.
AI Agent Instructions
The package includes an agent-readable instruction document for install, update, bootstrap, validation and context commands.
Give this short instruction to an agent that can inspect installed package resources:
Install `ai-docs-toolkit`, then configure this repository by following the packaged instructions in `ai_docs_toolkit/docs/agent-installation.md`.
After installation, an agent can locate it with:
python -c "from importlib import resources; print(resources.files('ai_docs_toolkit').joinpath('docs/agent-installation.md'))"
Operators can give the prompt from that document to an AI agent when asking it to install or update the toolkit in a consuming repository.
Development
Source checkout development install:
python -m pip install -e ".[dev]"
ai-docs --version
ai-docs validate
Current CI/source checkout install contract:
python -m pip install -e .
ai-docs validate --json
License
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