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Run AI coding workflows with specs, TDD, memory, and quality gates.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "pilot-shell" yet — see the docs or source repo.
Using the pilot-shell approach, design a development workflow for a new web app feature: first produce a requirements clarification checklist, then generate the technical plan, task breakdown, test plan, and acceptance criteria, while enforcing TDD throughout.
A spec-driven development plan with requirement checks, implementation steps, test cases, and acceptance gates.
Create execution rules for my AI coding agent: it must write the spec first, then failing tests, then implementation code, and finally run linting, type checks, unit tests, and a code review checklist; if any step fails, it must stop and report back.
An agent-ready rule set that makes code generation controlled, testable, and reviewable.
Generate a persistent memory template for our AI development assistant that records coding style, architectural constraints, common pitfalls, testing requirements, and release checks, and explain how to update this memory at the start and end of each task.
A maintainable project memory template that helps the agent preserve consistency and quality across iterations.
Bootstrap agentic TypeScript coding for Claude Code with workflows and quality checks.
Capture coding feedback and sync learned preferences into project memory files.
Turn approved specs into autonomous long-running implementation workflows and code output.
Standardize planning, memory, verification, and review across AI coding agents.
Provide coding rules and engineering guidance for AI coding agents.
Understand your codebase in terminal and accelerate coding with natural language.