669 件 ・ 関連度順
概要と使いどころ
Run development from an executable specification with traceable requirement IDs and merge-time coverage gates. Use when starting a greenfield feature, reviving a stale spec, or gating merges on requirement coverage.
日本語の概要は準備中です。原文の説明を表示しています。
Standardize SRS and FRS specifications for technical behavior, interfaces, data contracts, quality constraints, and verification mapping. Use when writing SRS, functional specification, system behavior requirements, API/data contracts, or non-functional thresholds.
日本語の概要は準備中です。原文の説明を表示しています。
Design specifications for effective dashboards. Use when planning new dashboards, improving existing ones, or documenting dashboard requirements before development starts.
日本語の概要は準備中です。原文の説明を表示しています。
Extract structured data from construction specifications. Parse CSI sections, requirements, submittals, and product data from spec documents.
日本語の概要は準備中です。原文の説明を表示しています。
Creates clear, testable specifications from feature descriptions with user stories. Use when starting a new feature and needing a spec before planning.
日本語の概要は準備中です。原文の説明を表示しています。
Converts a specification into a phased, dependency-ordered implementation plan. Use after specification is complete and before execution begins.
日本語の概要は準備中です。原文の説明を表示しています。
Design privacy API patterns including data subject API for DSAR endpoints, consent API for preference management, deletion API with cascading delete orchestration, and audit API for compliance reporting. Provides OpenAPI specifications, error handling, rate limiting, and authentication patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Master requirements gathering, user story writing, acceptance criteria definition, and scope management. Transform insights into clear, actionable specifications.
日本語の概要は準備中です。原文の説明を表示しています。
Builds a feature specification from scratch through a relentless, evidence-based interview that walks the design tree decision-by-decision, resolving dependencies as it goes. Use when the user wants to plan, design, scope, specify, or flesh out a new feature, capability, or system behavior before implementation. Produces a feature specification focused on system behaviors, not implementation detail. Does not plan a restructure of code that already exists — use plan-a-change. Does not refine or stress-test an existing plan — use iterative-plan-review. Does not document already-built features — use project-documentation. Does not design the contract for an interface — use design-an-api. Does not research open-ended options before there is a feature to specify — use research. Does not map the bounded contexts of existing code — use ddd-analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Establish explicit traceability between formal specifications (preconditions, postconditions, invariants) and verified code components with their correctness proofs. Produce structured Markdown mapping reports showing verification coverage and proof evidence. Use when auditing formal verification, documenting verified systems, establishing traceability for certification, or when the user asks to map specifications to code, generate verification reports, or analyze verification coverage in Coq, Dafny, Isabelle, or other proof assistants.
日本語の概要は準備中です。原文の説明を表示しています。
Automatically generate TLA+ specifications from source code (C/C++, Python) for formal verification of distributed systems. Use when users need to: (1) Generate TLA+ specs from program implementations, (2) Model distributed systems, consensus protocols, or concurrent algorithms, (3) Extract state variables, actions, and invariants from code, (4) Create formal specifications for model checking with TLC, (5) Verify safety and liveness properties of distributed systems. Particularly effective for message-passing systems, replication protocols, consensus algorithms, and distributed transactions.
日本語の概要は準備中です。原文の説明を表示しています。
Converts pseudocode descriptions and algorithm specifications into complete, executable Java code. Use this skill when you need to implement algorithms from pseudocode, translate algorithm descriptions to Java, generate Java code from specifications, convert textbook algorithms to working code, or create executable implementations from high-level descriptions. Preserves logic and control flow while handling Java idioms, data structures, and includes test cases for verification.
日本語の概要は準備中です。原文の説明を表示しています。
Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Use when: (1) Users provide initial requirements that need refinement, (2) Requirements are vague, incomplete, or ambiguous, (3) Creating formal specifications from informal descriptions, (4) Identifying missing constraints, edge cases, or acceptance criteria, (5) Clarifying assumptions and implicit dependencies, or (6) Preparing requirements for design, implementation, or verification. Operates interactively: analyze → ask clarifying questions → refine based on responses.
日本語の概要は準備中です。原文の説明を表示しています。
Transforms natural language requirements (user stories, verbal descriptions, business rules) into formal specifications and constraints. Use when converting informal requirements into structured, testable specifications with explicit constraints. Outputs in multiple formats including BDD-style Given-When-Then, JSON Schema, and structured plain text requirements documents.
日本語の概要は準備中です。原文の説明を表示しています。
Generate formal specifications (definitions, predicates, invariants, pre/post-conditions) in Isabelle/HOL or Coq from informal requirements, source code, pseudocode, or mathematical descriptions. Use when users need to: (1) Formalize algorithms or data structures, (2) Create function specifications with contracts, (3) Generate predicates and properties for verification, (4) Translate informal requirements into formal logic, (5) Specify invariants for loops or data structures, or (6) Create formal definitions for mathematical concepts. Supports both Isabelle/HOL and Coq equally.
日本語の概要は準備中です。原文の説明を表示しています。
Generate complete, production-ready functions and classes from formal specifications, design descriptions, type signatures, or natural language requirements. Use this skill when implementing APIs from specifications, creating data structures from schemas, building classes from UML diagrams, generating code from contracts, or translating design documents into code. Supports multiple programming languages and follows language-specific best practices.
日本語の概要は準備中です。原文の説明を表示しています。
Detects and analyzes ambiguous language in software requirements and user stories. Use when reviewing requirements documents, user stories, specifications, or any software requirement text to identify vague quantifiers, unclear scope, undefined terms, missing edge cases, subjective language, and incomplete specifications. Provides detailed analysis with clarifying questions and suggested improvements.
日本語の概要は準備中です。原文の説明を表示しています。
Generate concrete counterexamples when formal verification, assertions, or specifications fail. Use this skill when debugging failed proofs, understanding why verification fails, creating minimal reproducing examples, analyzing assertion violations, investigating invariant breaks, or diagnosing specification mismatches. Produces concrete input values, execution traces, and state information that demonstrate the failure.
日本語の概要は準備中です。原文の説明を表示しています。
Debug proof failures using counterexamples from Nitpick (Isabelle) or QuickChick (Coq) to identify specification errors, missing preconditions, and proof strategy issues. Use when: (1) A proof attempt fails and you need to understand why, (2) Counterexamples are generated by Nitpick or QuickChick, (3) Specifications may be incorrect or incomplete, (4) Theorems need validation before proving, (5) Missing preconditions or lemmas need identification, or (6) Proof failures need explanation and correction suggestions. Supports both Isabelle/HOL and Coq equally.
日本語の概要は準備中です。原文の説明を表示しています。
Plan game UX, UI, and HUD design specifications. Use when the user says "lets create game UX", "design the HUD", "create UI specifications", or "help me plan the game UX"
日本語の概要は準備中です。原文の説明を表示しています。
Write detailed feature specifications with functional requirements, edge cases, data models, API contracts, and UX flows. Create comprehensive technical specifications that enable clear implementation.
日本語の概要は準備中です。原文の説明を表示しています。
Write comprehensive Product Requirements Documents with user stories, acceptance criteria, technical specifications, wireframe descriptions, and prioritization frameworks (RICE, MoSCoW). Create clear specifications for product teams.
日本語の概要は準備中です。原文の説明を表示しています。
Creates detailed technical specifications for software projects covering requirements, architecture, APIs, and testing strategies. Use when planning features, documenting system design, or creating architecture decision records.
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Apply requirement quality principles when generating or validating feature specifications. Enforces feature completeness, scenario structure, AC verifiability, feature independence, and implementation slice quality. Use when writing feature specs, validating existing requirements, or when the user mentions 'validate this spec', 'check this feature', 'requirement quality', 'is this spec complete', or 'requirement-quality'. This skill governs the craft of writing individual feature specifications — not technical design (see design-blueprint), not implementation (see code-forge).
日本語の概要は準備中です。原文の説明を表示しています。