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Found 621 Skills
Write the full patent specification from claims and invention disclosure. Use when user says "撰写说明书", "write specification", "写说明书", "patent description", or wants to draft the complete patent specification.
Initialize and manage specification directories with auto-incrementing IDs. Use when creating new specs, checking spec status, tracking user decisions, or managing the docs/specs/ directory structure. Maintains README.md in each spec to record decisions (e.g., PRD skipped), context, and progress. Orchestrates the specification workflow across PRD, SDD, and PLAN phases.
Create GitHub Pull Request for feature request from specification file using pull_request_template.md template.
Create a new specification file for the solution, optimized for Generative AI consumption.
Transform project briefs into testable specifications with acceptance criteria. Use for requirements translation, spec creation, pre-implementation. Skip if spec exists or still exploring.
Translate PRDs into detailed UX specifications including user flows, screen descriptions, components, and interaction patterns. Use when a user has a PRD and needs to define the concrete UI/UX before generating development prompts. Bridges product requirements to implementation details.
Write technical specifications that give agents enough context to implement features while leaving room for autonomous research and decision-making. Use when planning features, documenting architecture decisions, or creating implementation guides.
Update an existing specification file for the solution, optimized for Generative AI consumption based on new requirements or updates to any existing code.
タスクを単一責務原則で分解しPhase 1-13の実行可能な仕様書を生成。Phase 12は中学生レベル概念説明を含む。 Anchors: • Clean Code / 適用: SRP / 目的: タスク分解基準 • Continuous Delivery / 適用: フェーズゲート / 目的: 品質パイプライン • DDD / 適用: ユビキタス言語 / 目的: 用語統一 Trigger: タスク仕様書作成, タスク分解, ワークフロー設計, Phase実行, IPC Bridge API統一, Preload APIパターン, safeInvoke, safeOn
Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.
Produce a one-page product intent specification with problem statement, users, metrics, risks, and acceptance criteria in Given/When/Then format. Use before any technical design or implementation work begins.
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.