@dtlabs/ai-toolkit — AI Toolkit

Reusable Claude Code agents, skills, commands, and procedures for end-to-end software feature delivery and codebase assessment — from requirements to PR, and from audit to remediation.

Meet Gaia — your toolkit assistant

Once installed, the best way to get started is to say hi:

/hi-gaia

Gaia is the toolkit's built-in assistant. She introduces herself, scans your workspace to understand the context (is the project already set up? are there features in progress?), and guides you toward the right tool for your situation.

You can also ask her about specific topics directly:

/hi-gaia feature       → how to build a new feature end-to-end
/hi-gaia assess        → how to audit and improve an existing codebase
/hi-gaia setup         → how to onboard a new project
/hi-gaia agents        → full catalog of available agents and skills

If you're ever unsure which command or agent to use, Gaia is the right starting point. She won't run anything — she helps you understand the toolkit and decide what to do next.

What it provides

Two independent pipelines:

Feature Delivery Pipeline

• 12 agents for the full delivery lifecycle (requirements → tech-spec → work breakdown → backend/frontend/testing implementation → architect review)
• 5 skills invocable via slash commands (/install-toolkit, /init-agents, /implement-feature, /define-feature, /hi-gaia)
• 4 commands for quick day-to-day shortcuts (/feature-status, /check-docs, /pr-description, /next-task)

Assessment & Remediation Pipeline

• 10 agents for codebase assessment and targeted remediation (generic assessment, layer audit, concurrency safety, god class decomposition, DI refactoring, domain model refactoring, security hardening, supply chain security, intervention documentation)
• 1 skill (/assess-codebase) that runs the full assessment pipeline with a human approval gate before any code changes
• 1 command (/assessment-status) for checking the state of an ongoing assessment

Shared

• 4 generic procedures (code generation, code review, secure coding, testing) that projects can override locally

Install

Local installation (into the current project):

npx @dtlabs/ai-toolkit

Global installation (into ~/.claude/):

npm install -g @dtlabs/ai-toolkit
ai-toolkit --global

Both commands copy agents, skills, procedures, and CLAUDE.md into the appropriate location.

How it works

The toolkit ships generic agents that work with any project. Each agent reads project-specific conventions from an AGENTS.md file in the consuming project's root. Run /init-agents to generate that file for a new project.

Generic procedures live in docs/procedures/. Projects can override any of them by placing a file with the same name at their own docs/procedures/. Agents check the project first, then fall back to the toolkit.

Documentation

• Quick Reference — cheatsheet of every skill, command, agent, and procedure
• Installation guide — full .npmrc setup and CLI options
• CLAUDE.md — agent and skill reference
• docs/procedures/ — reusable workflows

License

MIT