commit-chunks
Review and commit changes in meaningful chunks. Use when the user has multiple uncommitted changes that should be organized into logical, atomic commits.
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Review and commit changes in meaningful chunks. Use when the user has multiple uncommitted changes that should be organized into logical, atomic commits.
Review and commit git changes in meaningful, atomic chunks. Use when a user asks to review uncommitted changes, group them into logical commits, stage selectively, and create conventional-commit messages, inclu...
Delegates coding tasks to Coco CLI (Codebase Copilot) for prototyping, debugging, and code review. Use when needing algorithm implementation, bug analysis, or code quality feedback. Supports multi-turn sessions...
AI-powered code indexer with semantic search, knowledge graphs (GraphRAG), and persistent memory system. Use when you need to (1) perform semantic code searches across large codebases, (2) analyze file relation...
sdd-initで作成したSpecドラフトを入力として、TDDを回せるだけのテスト観点(ハッピー/代表的失敗/境界/不変条件/非機能)をSpecに網羅する。ここではテスト実装・プロダクション実装は行わない。スコープ変更・要件追加もし...
sdd-slice-wishで決めた「推奨スライス」を入力として、仕様書 docs/specs/YYYYMMDD-{name}.md のドラフトを作成する。ここでは実装もテスト実装も行わない。テストケースの網羅(境界・異常・不変条件の列挙)は sdd-test-cas...
TDDのリファクタ(REFACTOR)フェーズを厳密に実行する。全テストGREENを維持したまま、重複排除・命名改善・関心分離など内部構造を改善する。仕様変更が必要なら先にSpecとテスト期待値を更新してから実装を調整する。
TDDのグリーン(GREEN)フェーズを厳密に実行する。REDの「1本だけ」失敗しているテストを通すために、最小限のプロダクションコードだけを実装し、全テストGREENを確認する。余計な機能追加・設計改善はしない。
大きな「やりたいこと」を、1Spec=1PRとしてレビュー可能・検証可能・安全にマージ可能なサイズへスライスする。ここでは具体的な仕様書(受入条件の詳細化・テスト観点の網羅・docs/specs/* の作成)は行わない(それは sdd-i...
TDDのレッド(RED)フェーズを厳密に実行する。Spec/受入条件から「1つ」選び、失敗するテストを「1本だけ」追加して実行し、失敗(RED)を確認する。仕様が不明瞭なら実装に進まず、質問/Spec更新提案を行う。
Rustでのエラー設計を、境界ごとに thiserror / anyhow を使い分けて実装する。ドメイン/ライブラリは型付きエラー(thiserror)、アプリ境界のみ anyow。context付与、unwrap禁止、HTTP/CLI変換の指針を含む。
Search and retrieve official Microsoft documentation, code samples, and technical information. Use PROACTIVELY when researching Azure AI Search, Copilot Studio, Azure Cognitive Services, Azure App Service, Micr...
Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'...
Refactoring patterns and best practices for creating maintainable geometry MicroSims using p5.js. Provides guidelines for local coordinate systems, push/pop/translate/scale patterns, mathematical accuracy, and...
Generate comprehensive specification documents including requirements, technical design, and detailed task breakdown from any feature request. Use when the user asks to create specs, requirements docs, design d...
Comprehensive guide for building Agent Skills according to agentskills.io specification. Use when developers need to create, structure, or validate skills that follow the Agent Skills standard format and best p...
Expert on wgpu GPU rendering, WGSL shaders, and GPU pipeline configuration. Use when discussing rendering, shaders, GPU, textures, or graphics pipeline.
Expert on FLUI's reactive state management with signals, hooks, and effects. Use when discussing state, signals, use_signal, use_effect, reactivity, or data flow.
Expert on FLUI's three-tree architecture (View-Element-Render), widget composition, and Flutter-inspired patterns. Use when discussing views, elements, render objects, widget trees, or UI architecture.
Analyzes Rust code for performance bottlenecks, memory inefficiencies, and optimization opportunities. Use when discussing performance, slow code, memory usage, profiling, benchmarks, or optimization.
Convert documents between formats using Pandoc. Use when the user asks to convert files between formats like markdown, docx, html, pdf, latex, epub, rtf, csv, xlsx, or pptx. Triggers on requests like "convert t...
Extract clean article content from URLs and save as markdown. Triggers when user provides a webpage URL and wants to download it, extract content, get a clean version without ads, capture an article for offline...
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when "installing spaCy", "selecting model for nlp" (en_core_web_sm/md/lg/trf), "tokenization", "POS tagging", "name...
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.