2.8万 件 ・ 関連度順
概要と使いどころ
MATLAB R2026a code generation and deployment workflow for MATLAB Coder, Simulink Coder, Embedded Coder, GPU Coder, HDL Coder, fixed-point conversion, MEX validation, and embedded deployment readiness. Use whenever the user asks to generate C/C++/CUDA/HDL/code, deploy algorithms, or validate generated 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。
Guide for simplifying and refining code after coding sessions. Use when cleaning up complex code, reviewing PRs for readability, or applying consistent refactoring patterns. Triggers on simplify code, refactor, clean up, code review, コード整理, リファクタ, 複雑さ削減, コードレビュー.
Review code for quality, bugs, and design issues. Use when the user says "review this code", "do a code review", "check this PR", "review this diff", "is this code good", "what's wrong with this code", "code quality check", or pastes code and wants feedback - even if they don't explicitly say "code review".
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 this skill when running local AI models with Docker Model Runner — the `docker model` CLI — e.g. "run an LLM locally with Docker", "pull a model from the ai/ namespace", "connect my app to a local model", "use a local model as backend for the Drupal AI module", or when wiring the `models:` top-level element into a compose.yaml. Covers pulling/running models, OpenAI-compatible endpoints, and Compose integration.
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。
A workflow skill that lets Codex keep coding for 60 hours on medium and large projects: Claude Code CLI plans through an interactive requirements questionnaire, PRD, specs, and roadmap; Codex implements verified vertical slices, with resumable Long-Run Execution for lengthy work; Trellis maintains project memory. Use when the user mentions 大项目工作流, Codex 连续开发 60 小时, Codex 长任务, long-running or resumable Codex implementation, large/medium project, new SaaS, multi-module system, requirements questionnaire, Claude Code CLI planning, Codex implementation handoff, Trellis bootstrap, non-system-drive project, or vertical slice. Skip for: single-file edits, casual Q&A, copy polish, throwaway prototypes, or tasks the user explicitly wants done fast without process.
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。
codex:codex-rescueエージェントを起動する各スキル(codex-review-loop・codex-consult等)が共有する、ハング防止付きの起動・監視・再試行契約の正本。内部専用でユーザーが直接使うものではない。
Knowledge base from the NASA Systems Modeling Handbook for Systems Engineering (NASA-HDBK-1009A Rev A, 2025). Use for model-based systems engineering (MBSE) wired into NASA's NPR 7123.1 SE processes: the three aspects of MBSE (language / methodology / framework), the NASA SE Engine and its two OOSEM-derived steps (Model Planning, Setting Up the Model), the Modeling Plan as a SEMP subset, the tool-agnostic NASA SE metamodel of elements and relationships across the four SysML pillars (structure / behavior / requirements / parametrics), worked SysML diagrams and tables for stakeholders, requirements, structure and V&V, generating SE work products (ConOps, MOE, MOP, TPM, V&V), the MBSE Grid framework, alternative modeling approaches (PBR, Scenario, System Specification, Verification), and the ConOps model-content template. Scope is bounded to four common technical processes (Stakeholder Expectation Definition, Technical Requirements Definition, Product Verification, Product Validation). Does NOT teach SysML itself, mandate a tool, define NPR 7123.1 processes, cover technical-management processes 10-17, or reproduce the OMG SysML specification.
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。
Configures Codemagic CI/CD pipelines for Flutter using `codemagic.yaml`. Use when setting up automated Flutter builds on Codemagic, configuring iOS code signing without Fastlane Match, deploying to App Store Connect or Google Play from Codemagic, caching pub dependencies in Codemagic, setting up encrypted environment variable groups, running tests with Codemagic's test dashboard, or choosing between Codemagic and GitHub Actions + Fastlane for a Flutter CI/CD pipeline.
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 working with Codescene — codeScene behavioral code analysis including code health scoring, hotspot detection, change coupling analysis, and PR integration for code quality gates. Use when configuring CodeScene for codebase visualization, technical debt prioritization, and automated code review feedback.
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 and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
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。
Runs a comprehensive 20-point code quality audit on a "vibe-coded" codebase that was shipped fast and now needs hardening. Use this skill whenever the user mentions vibe coding, vibe audit, code audit, code review, code cleanup, hardening a prototype, productionizing a codebase, technical debt cleanup, or asks Claude to "audit my code", "review my codebase", "clean up my project", or check a freshly-shipped project for common quality issues. Also use when a user shares a repo and asks what's wrong with it or how to make it production-ready.
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。
Claude API (platform.claude.com) のモデル・SDK リファレンス。 モデル選択基準・model ID とバージョン・Fable 5 / Mythos 5 / Opus 5 / Sonnet 5 の新機能・移行ガイド、 pricing・model deprecation・用語集を含む。 公式 SDK 7 言語（Python / TypeScript / Java / Go / Ruby / C# / PHP）、 Claude API 用 CLI（`ant`、Claude Code CLI とは別）の quickstart / authentication / scripting、 middleware、OpenAI SDK 互換レイヤー、Apple Foundation Models 連携を含む。
Pick the right business-model canvas (Lean Canvas, Business Model Canvas, or Value Proposition Canvas) for the stage and fill it with specifics — one segment, one primary canvas, top-3 assumptions, no fluff in the moat or channel boxes. Load when the user asks to fill a business model canvas, lean canvas, value proposition canvas, model this business, map the business model, says "fill the BMC", "make a Lean Canvas", "Value Proposition Canvas for this", "model this idea", "what's the business model", "design the business model". Sub-skill of `venture-exploration`. Hard-bans "everyone" segments, generic channels ("SEO/social/content/ads"), and "unfair advantage = AI/data/network effects" with no concrete asset. Does NOT score viability — for that use `idea-evaluation`.
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。
Codex が設計・実装を担い、Claude が要件確定・成果物の検証・反復・commit/push を管理する。「codex に書かせて」「codex メインで実装」「codex-drive」で発火。大きめの機能・移植・プロトコル実装向け。余剰トークンを厚く使う運用も選べる。
Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
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。
[BETA] Detect, review, and fix code-quality and correctness issues in an AEM as a Cloud Service project — locally, with no external services or network calls. Use whenever a user wants to check, review, assess, audit, scan, modernize, upgrade, or fix AEM Java, Sling Models, OSGi, or Maven code — for example: "check my Sling Models are implemented correctly", "review my @Inject usage", "are my Maven dependencies up to date", "scan this AEM project for issues", "modernize my Sling Models", or "fix code-quality problems". Name the files to assess, or ask it to scan the repo; it detects issues, plans, and — only when you ask — applies surgical edits on a branch or in place, then verifies with mvn compile. It recognises the intent and handles each issue type itself, reporting anything it cannot yet fix. This skill is in beta. Verify all outputs before applying them to production projects.
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。
Shellcode development reference for offensive security engagements. Use when writing custom x86/x64 shellcode, implementing position-independent code (PIC), building shellcode loaders, evading AV/EDR detection, or converting PE files to shellcode. Covers null byte avoidance, API hashing, encoder/decoder patterns, staged vs stageless payloads, Windows PEB traversal, and cross-platform shellcode techniques.
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。
OpenClawにモデル提供サービスを追加し、実際の応答まで確認するスキル。認証情報は環境変数やファイルへの参照で扱い、設定の検証と結果報告も進めます。
Everything Claude CodeのスキルとフックをDeepSeek Harnessへ導入し、設定の生成・動作確認・更新から、認識されない場合の原因調査まで案内します。
作業環境の設定や接続済みツールを読み取り、今使える機能と不足を整理するスキル。Claude Codeなどで次に整えるECCのスキルや連携を提案します。
SF SymbolsやIconify APIからiOS・macOS向けのアイコンを選び、既存の配色やサイズに合わせてXcode用のPNG素材一式を生成するスキル。
iOS 26以降のアプリに、端末内で動く言語モデルを組み込むスキル。文章生成・要約、入力からのデータ抽出、独自処理の呼び出し、生成中の画面更新を扱います。
複数の視点でまとめた重要な意思決定の草案に、Codexによる外部批評を一度追加します。結論の弱点や見落とし、反対意見の扱いを確認するスキルです。
AIが修正したコードで同じ不具合が再発しないよう、APIの必須項目や処理分岐を自動テストで確認し、テストとビルドを先に行うレビュー手順を整えるスキル。