4,006 件 ・ 関連度順
概要と使いどころ
Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach.
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 spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.
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。
Use when implementing any feature or bugfix, before writing implementation code. Enforces RED-GREEN-REFACTOR cycle with test-first approach.
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。
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
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。
Delegate coding tasks to OpenCode CLI agent for feature implementation, refactoring, PR review, and long-running autonomous sessions. Requires the opencode CLI installed and authenticated.
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。
Delegate coding tasks to Claude Code (Anthropic's CLI agent). Use for building features, refactoring, PR reviews, and iterative coding. Requires the claude CLI installed.
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。
Delegate coding tasks to OpenAI Codex CLI agent. Use for building features, refactoring, PR reviews, and batch issue fixing. Requires the codex CLI and a git repository.
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。
Create a detailed, phased implementation plan with documentation discovery. Use when asked to plan a feature, task, or multi-step implementation — especially before executing with do.
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。
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score 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。
Generates a Python CLI tool for bidirectional conversion between 4-byte floating-point numbers and hexadecimal memory representations, featuring a continuous loop and robust input parsing.
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。
Use when implementing any feature or bugfix, before writing implementation code
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。
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
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。
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety 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。
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before 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。
Generates user-facing changelogs and release notes from git commit history. Parses conventional commits, categorizes changes into features, fixes, breaking changes, and more, then rewrites technical messages into customer-friendly language. Use when the user asks to generate a changelog, write release notes, summarize recent commits, prepare CHANGELOG.md, or document what changed between versions.
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 a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
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。
Interactive Product Owner skill for requirements gathering, analysis, and PRD generation. Triggers when users request product requirements, feature specification, PRD creation, or need help understanding and documenting project requirements. Uses quality scoring and iterative dialogue to ensure comprehensive requirements before generating professional PRD 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。
Breaks down trading ideas into component parts for systematic Pine Script implementation. Use when analyzing trading concepts, decomposing strategies, planning indicator features, or extracting ideas from YouTube videos. Triggers on conceptual questions, "how would I build", YouTube URLs, or video analysis requests.
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 strategy-oriented Product Requirements Documents (PRDs) for AI product managers. Use when: (1) drafting a new PRD or strategy doc, (2) structuring a feature proposal with strategy rationale, (3) writing requirement docs that emphasize "why" over "how", (4) turning raw product ideas into structured requirement documents. NOT for: purely technical specs, engineering tickets, or UI copy.
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。
在任何创意性工作前必须使用：创建功能、构建组件、增加能力或修改行为。通过自然对话挖掘需求，产出高质量验收标准（AC），为后续 TDD 开发提供测试依据。当用户说'我想做一个XX功能'、'帮我想想XX怎么做'、'我需要加一个XX'等模糊需求描述时触发。
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。
Complete API for Google NotebookLM - full programmatic access including features not in the web UI. Create notebooks, add sources, generate all artifact types, download in multiple formats. Activates on explicit /notebooklm or intent like "create a podcast about X"
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。
Decide what to build — product strategy, roadmap, feature prioritization, product-market fit, pricing model, backlog, sprint planning, product vision, RICE, JTBD, OKRs. Distinct from designing or building it.
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。
SEO, AEO and GEO — search, keywords, ranking, visibility, answer engine optimization, generative engine optimization, voice search, organic traffic, featured snippets, technical search audit, E-E-A-T, structured data.
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。
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
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。