Implementation entry point. Use to execute a completed specification. Reads the spec's slice and scenario tasks from the tracker, then runs a dynamic workflow that builds each phase's slices and evaluates the phase through a barriered code→eval retry loop…
Create and validate solution design documents (SDD). Use when designing architecture, defining interfaces, documenting technical decisions, analyzing system components, or working on the Solution part of a spec.md in .start/specs/.
Author the implementation plan — the Plan part of spec.md (target state + phases) plus the implementation TASKS in the spec's tracker that /implement runs. Each phase task holds slice tasks whose bodies are code briefs (features + EARS behavior + quality…
Use when completing implementation, fixing bugs, refactoring code, or any time you need to verify the test suite passes. Also use when tests fail and you hear "pre-existing" or "not my changes" — enforces strict code ownership. Ensures MECE coverage (no…
Consolidate a completed specification into a single archived record and remove its working directory. Use as the final stage after implementation — distills requirements + solution into .start/archive/[NNN]-[name].md and deletes the .start/specs/[NNN]-[name]/…
Scaffold, status-check, and manage specification directories. Use when creating a new spec, reading spec status, transitioning between phases, or logging decisions on a spec in .start/specs/.
Create and validate product requirements documents (PRD). Use when writing requirements, defining user stories, specifying acceptance criteria, analyzing user needs, or working on the Requirements part of a spec.md in .start/specs/.
Create a comprehensive specification from a brief description. Opens by clarifying intent — surfacing unknowns and assumptions before anything is written — then runs requirements gathering (WHY), solution design (WHAT — target architecture), and the…
Validate in any of six modes — spec quality, single-file review, spec-to-implementation drift, constitution rule enforcement, comparison between two artifacts, or sanity-checking your understanding. Use when checking a spec by ID, validating a file by path,…
Deep-research analysis of a codebase, a topic, or both. Clarifies the question, agrees the research angles with you, then runs a dynamic workflow that gathers cited claims per angle, merges duplicates, has independent skeptics try to refute every claim, and…
Required first step before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
Self-improvement from this project's Claude Code session logs. Mines a date range (default "yesterday") through parallel signal lenses, clusters what it finds into improvement opportunities, drafts a concrete change per opportunity, adversarially validates…
Evidence-based code review. Resolves the review scope (PR, branch, staged changes, paths, or a freeform description), detects the stack from project instructions and the changed files, picks the review dimensions and any installed specialist agents, confirms…
Find deepening opportunities in a codebase — refactors that turn shallow modules into deep ones for better testability and AI-navigability. Use when the user wants to improve architecture, surface architectural friction, consolidate tightly-coupled modules,…
Context enrichment for agentic AI application development using LangChain, Vercel AI SDK, and assistant-ui. Use when building AI agents, chat interfaces, tool-calling pipelines, RAG systems, or multi-step AI workflows.
Context enrichment for frontend UI development using shadcn/ui and Tailwind CSS. Use when building component libraries, implementing UI designs, theming, or working with accessible React components.
Unified platform operations guidance for CI/CD pipeline design, deployment strategies, observability, SLI/SLOs, and incident-ready rollouts. Use when building release workflows, production monitoring, or reliability controls.
Unified codebase discovery across structure navigation, tech-stack detection, and documentation extraction. Use when onboarding to a project, locating implementation paths, identifying frameworks/tooling, or validating docs against code reality.
User research and insight synthesis for interviews, usability testing, personas, journey mapping, and actionable product/design recommendations. Use when planning studies, collecting evidence, synthesizing patterns, or converting findings into prioritized…
Unified domain and data modeling for business entities, invariants, schema design, aggregate boundaries, and evolution strategy. Use when designing business models, schema changes, bounded contexts, or consistency rules.
RICE, MoSCoW, Kano, and value-effort prioritization frameworks with scoring methodologies and decision documentation. Use when prioritizing features, evaluating competing initiatives, creating roadmaps, or making build vs defer decisions.
Identify existing codebase patterns (naming conventions, architectural patterns, testing patterns) to maintain consistency. Use when generating code, reviewing changes, or understanding established practices.
Requirement gathering techniques, stakeholder analysis, user story patterns, and specification validation. Use when clarifying vague requirements, resolving conflicting needs, documenting specifications, or validating requirements with stakeholders.
REST and GraphQL API design patterns, OpenAPI/Swagger specifications, versioning strategies, and authentication patterns. Use when designing APIs, reviewing API contracts, evaluating API technologies, or implementing API endpoints.
System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Use when designing system architectures, evaluating patterns, or planning scalability.
Create architectural decision records (ADRs), system documentation, API documentation, and operational runbooks. Use when capturing design decisions, documenting system architecture, creating API references, or writing operational procedures.
Writing effective tests and running them successfully. Covers layer-specific mocking rules, test design principles, debugging failures, and flaky test management. Use when writing tests, reviewing test quality, or debugging test failures.
Measurement approaches, profiling patterns, bottleneck identification, and optimization guidance. Use when diagnosing performance issues, establishing baselines, identifying bottlenecks, or planning for scale. Always measure before optimizing.