484 skills · sorted by relevance
Create and maintain OpenAPI 3.1 specifications from existing code or initial designs. Use these API descriptions to prepare documentation, generate client SDKs—libraries for calling an API—and check whether implementations match their specifications.
Turn a product's visual and interaction goals into DESIGN.md and EXPERIENCE.md. Through guided discussion, capture appearance, screen structure, behavior, accessibility, and user journeys as specifications that can guide later design and development work.
Update main specifications from delta specs, documents describing intended changes. Apply requirement additions, edits, removals, and renames while preserving unrelated content and keeping the change active for further implementation work.
Define reusable OpenRig agent setups, roles, and workflows in specification files. Review dependencies that prevent use on another host, distinguish specifications from bundles and extensions, and verify both file structure and actual execution.
Extract structured product details from Walmart URLs, including prices, availability, specifications, images, and color or size options. Gather fulfillment choices, return policies, and review summaries to support product comparisons and catalog building.
Update main specifications from delta specs, documents describing intended changes. Apply requirement additions, edits, removals, and renames while preserving unrelated content and keeping the change active for further implementation work.
要件定義と実装の間を埋める技術仕様書を体系的に作成するスキル。 画面設計、API設計、DB設計、シーケンス図、状態遷移図をMermaid形式で生成し、 IEEE 830/ISO 29148準拠の仕様書を出力する。Use when creating functional specifications, API design documents, database design documents, screen design specifications, or sequence/state diagrams from requirements. Triggers: "technical specification", "functional spec", "API design", "database design", "screen design", "画面設計書", "API設計書", "DB設計書", "技術仕様書", "シーケンス図", "状態遷移図"
The English summary is being prepared. Showing the original description.
Create a product launch email in HTML with a brand wordmark, product visual, headline, specifications, and one main call-to-action button. The centered, single-column layout brings the product message together in a complete email design.
Create API specifications, interactive documentation, and developer portals that explain how to use an API. The skill also covers authentication examples, SDK generation, example testing, and migration guides to help developers integrate and maintain their applications.
Turn a system description into REST API endpoints, the URLs and operations applications use to exchange data. Choose an endpoint list or detailed specifications covering authentication, request fields, responses, error codes, and pagination for lists.
Review skill and agent definitions for structural issues and whether their instructions meet expected behavior. Four modes cover structure, test specifications, category criteria, and coverage reports that reveal missing specifications or checks.
Turn game design documents and character profiles into asset specifications and image generation prompts. Define appearance, dimensions, file formats, and naming rules, then maintain an asset list that tracks progress and identifies shared assets.
Create HTML or plain-text emails from JSON specifications with React Email. This skill guides reusable email components, conditional content, server-side rendering, and browser previews for transactional messages such as signup notifications and marketing emails.
Design REST or GraphQL APIs by defining data relationships, requests, responses, and authentication. Produce OpenAPI specifications, machine-readable API descriptions, with consistent errors, pagination, and versioning plans, then validate contracts using a mock server.
Writes and reviews Lean 4 proofs, machine-checked arguments for mathematics or specifications. Follows Mathlib conventions to organize definitions and lemmas, fill proof gaps, refactor lengthy proofs, and establish automated checks for unproved claims and style.
Collect Amazon product data from ASINs, unique product identifiers, and compare prices, specifications, reviews, and product images. Produce comparison tables and reports that highlight competitive strengths, weaknesses, and potential market opportunities.
Extract Amazon search results with product titles, prices, ratings, identifiers, and available specifications. Set keywords, brand, page count, and browsing language to gather structured information for market research, competitor comparisons, and product catalog updates.
Generate comprehensive test case documentation from test code, test framework output, existing test docs, and source code context. Use when documenting test suites, creating test specifications, generating test coverage reports, onboarding developers to testing practices, or preparing QA documentation. Analyzes test functions (pytest, unittest) to extract test names, docstrings, assertions, and organization, then produces structured markdown with both overview-level summaries and detailed test case specifications including purpose, preconditions, steps, expected results, and test data. Triggers when users ask to document tests, generate test specifications, create test reports, summarize test coverage, or explain what tests do.
The English summary is being prepared. Showing the original description.
Verify code correctness statically against specifications using type checking, contract verification, and formal methods. Use when: (1) Verifying type safety and null safety in Python, Java, or C/C++ code, (2) Checking design-by-contract specifications (preconditions, postconditions, invariants), (3) Validating code against formal specifications, (4) Ensuring code quality and correctness before runtime, (5) Finding potential bugs through static analysis. Supports Python (mypy, contracts), Java (javac, JML), and provides verification scripts and contract specification guidelines.
The English summary is being prepared. Showing the original description.
Automatically simplify and minimize TLA+ specifications by reducing redundant state variables, merging equivalent actions, and minimizing invariants while preserving specified properties. Use when working with TLA+ specifications that need optimization, simplification, or reduction. Triggers when users ask to minimize, reduce, simplify, or optimize TLA+ specs, or when they want to remove redundancy from formal specifications while maintaining semantic equivalence.
The English summary is being prepared. Showing the original description.
Generate systematic refinement steps from high-level specifications to concrete implementations in Isabelle/HOL or Coq, preserving correctness obligations at each step. Use when working with formal verification, program refinement, proof development, or when translating abstract specifications into executable code while maintaining formal guarantees. Supports data refinement (abstract types → concrete structures), algorithmic refinement (specifications → algorithms), and stepwise refinement with proof obligations.
The English summary is being prepared. Showing the original description.
Convert pseudocode, algorithm descriptions, or specifications into complete, executable Python code. Handles natural language descriptions, structured pseudocode, and formal algorithm specifications. Generates production-ready code with type hints, docstrings, error handling, and test cases. Use when users need to (1) convert pseudocode to Python, (2) implement algorithms from descriptions, (3) translate algorithm specifications to code, (4) generate Python implementations from textbook pseudocode, or (5) create executable code from high-level algorithm designs.
The English summary is being prepared. Showing the original description.
Check behavioral consistency between high-level hardware specifications and RTL implementations. Use when asked to check RTL consistency, verify RTL against spec, check hardware specification compliance, validate RTL implementation, find spec violations in RTL, check behavioral consistency, or when working with hardware designs that need verification against protocol specifications, timing requirements, or functional specifications in Verilog, VHDL, or SystemVerilog.
The English summary is being prepared. Showing the original description.
Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.
The English summary is being prepared. Showing the original description.