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Found 505 Skills
OpenAPI (Swagger) 2.0 specification for describing REST APIs. Use when writing, validating, or interpreting Swagger 2.0 specs, generating clients/docs, or working with path/operation/parameter/response/schema/security definitions.
Use when acting as Grunk - reads specs from beads, plans, implements, commits, tags pr-ready. Merged TL+Engineer. Works in loop mode or interactive mode.
React PDF renderer for json-render. Use when generating PDF documents from JSON specs, working with @json-render/react-pdf, or rendering specs to PDF buffers/streams/files.
Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Trigger when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document page logic, analyze page fields and interactions, create a functional inventory, write requirements from an existing codebase, document API endpoints, or analyze backend routes.
Explore any codebase from scratch and generate six quality artifacts: a quality constitution (QUALITY.md), spec-traced functional tests, a code review protocol, an integration testing protocol, a multi-model spec audit (Council of Three), and an AI bootstrap file (AGENTS.md). Works with any language (Python, Java, Scala, TypeScript, Go, Rust, etc.). Use this skill whenever the user asks to set up a quality playbook, generate functional tests from specifications, create a quality constitution, build testing protocols, audit code against specs, or establish a repeatable quality system for a project. Also trigger when the user mentions 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', 'coverage theater', or wants to go beyond basic test generation to build a full quality system grounded in their actual codebase.
Create a ***plain import module that provides shared definitions, implementation reqs, and test reqs for other modules to import. Use when the user wants to create a new .plain file that contains only definitions, implementation reqs, and/or test reqs — no functional specs.
Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.
Add multiple functional specs to the ***functional specs*** section of a ***plain spec file in a single batch. Use whenever more than one new functional spec is being added — whether the user explicitly asks, or another skill/workflow (e.g. forge-plain, add-feature) needs to author several specs in one pass. Bulk-writing or hand-authoring functional specs without invoking this skill is forbidden; for adding a single spec, use add-functional-spec instead.
Use when a spec or plan needs review before execution begins - "review my spec", "is this plan ready to execute", "check this before I build it", "second opinion on this plan" - and specifically before writing-plans (spec mode) or before subagent-driven-development (plan mode). Reviews specs and plans, not code. Panels six reviewers across two model tiers (cross-vendor configurable) and three topics, invokes a reasoning-tier juror only when the tiers disagree, and gates the next workflow step with a fail-closed Blockers / Warnings / Observations verdict.
Use when stories, specs, BRDs, APIs, workflows, or equivalent delivery artifacts exist and you need to review them for testability, missing business rules, unclear behavior, scope ambiguity, and QA blocking gaps before generating tests. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.
Interview the operator and write the strategic layer of a product —vision, problem, users, scope, competitors, opportunities, open questions, glossary— into the `context/` of its node in the brain, never into the body repo. Manually triggered, last link of the discovery pipeline and the gate before specs.
Product requirements and planning specialist. Creates PRDs and tech specs with functional/non-functional requirements, prioritizes features using MoSCoW/RICE frameworks, breaks down epics into user stories, and ensures requirements are testable and traceable. Use for PRD creation, requirements definition, feature prioritization, tech specs, epics, user stories, and acceptance criteria.