ai-devkit
v0.69.1
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Make AI coding agents follow a repeatable engineering workflow with memory, verification, skills, and multi-agent setup
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AI DevKit CLI
The command-line interface for AI DevKit — make AI coding agents follow a repeatable engineering workflow in your project.
Use this package when you want the ai-devkit command to install agent skills, memory, verification gates, MCP configuration, and docs/ai/ workflow files into a project.
Features
- Workflow layer — Requirements, design, planning, implementation, testing, verification, and review
- AI environment setup — One-command configuration for Cursor, Claude Code, Codex, Gemini CLI, Devin, and other agents
- Skill management — Install reusable AI skills that change agent behavior
- Persistent memory — Store project decisions and conventions so agents can reuse them across sessions
Installation
# Run directly (no install needed)
npx ai-devkit@latest init
# Or install globally
npm install -g ai-devkitQuick Start
# Set up your project interactively
ai-devkit init
# Set up from template (no step-by-step prompts when template is complete)
ai-devkit init --template ./ai-devkit.init.yamlThis will:
- Create a
.ai-devkit.jsonconfiguration file - Set up your AI coding agent environment, including skills and MCP servers where supported
- Generate
docs/ai/workflow docs for requirements, design, planning, implementation, and testing - Give your agent a repeatable process instead of relying on one-off chat instructions
After initialization, your repo gets project-local files you can review and commit:
your-project/
├── .ai-devkit.json
├── .claude/ # or .cursor/, .codex/, etc. based on selected agents
│ ├── skills/
│ └── settings.json
└── docs/ai/
├── requirements/
├── design/
├── planning/
├── implementation/
└── testing/In your AI editor, ask the agent to use the dev-lifecycle skill to clarify the feature before editing code.
Common Commands
# Initialize project
ai-devkit init
# Initialize project from YAML/JSON template
ai-devkit init --template ./ai-devkit.init.yaml
# Install/reconcile project setup from .ai-devkit.json
ai-devkit install
# Overwrite all existing install artifacts without extra prompts
ai-devkit install --overwrite
# Add a development phase
ai-devkit phase requirements
# Validate workspace docs readiness
ai-devkit lint
# Validate a feature's docs and git branch/worktree conventions
ai-devkit lint --feature lint-command
# Emit machine-readable output for CI
ai-devkit lint --feature lint-command --json
# Probe capacity for every supported provider (codex, z.ai, OpenAI, Claude)
ai-devkit capacity
# Probe a single provider's capacity
ai-devkit capacity zai
# Claude uses CLAUDE_CODE_OAUTH_TOKEN, the active profile file, or the
# default-profile macOS Claude Code Keychain item
ai-devkit capacity claude
# Emit the JSON report (single object for one provider, array for many)
ai-devkit capacity codex --json
# Install a skill
ai-devkit skill add <skill-registry> [skill-name]
# List skills installed across known global environment paths
ai-devkit skill list --global
# Limit global listing to selected environments
ai-devkit skill list --global --env claude codex
# Store project knowledge for future agent sessions
ai-devkit memory storeOn macOS, the operating system may request Keychain access the first time the Claude fallback is used. Custom CLAUDE_CONFIG_DIR profiles use only their own credentials file and never the global Keychain item.
UI Formatting Standards
Shared CLI presentation helpers live in src/util/. Commands should use
status.ts for status labels and chalk colors, time-format.ts for relative
or Mon D · HH:mm time labels with an injectable now clock, and
pluralize.ts for count labels. Keep JSON output independent from these
terminal-only helpers so machine-readable shapes stay stable.
Template example:
version: 1
environments:
- codex
- claude
phases:
- requirements
- design
- planning
- implementation
- testing
skills:
- registry: codeaholicguy/ai-devkit
skill: dev-lifecycle
- registry: codeaholicguy/ai-devkit
skill: verify
- registry: codeaholicguy/ai-devkit
skill: memory
- registry: codeaholicguy/ai-devkit
skill: tddDocumentation
📖 For the full user guide, workflow examples, and best practices, visit:
License
MIT
