エージェントスキルとは何ですか？
エージェントスキルは、AI エージェントが必要なときに読み込む再利用可能な機能パッケージです。一般に SKILL.md ファイル、操作手順、ワークフロー、スクリプト、任意のリソースが含まれます。タスクがスキルの説明に一致すると、エージェントは関連コンテンツを読み込んで専門的な作業を行います。
スキル
インストールコマンド、ソースリポジトリ、ユースケース、セキュリティ情報付きで、Claude スキル、Codex スキル、再利用可能なエージェントスキルを見つけましょう。
データ＆データベース
公式
microsoft-foundry
microsoft / azure-skills
Deploy, evaluate, fine-tune, and manage Foundry agents end-to-end with azd: hosted agent scaffold/run/deploy, prompt agent create, batch eval, continuous eval, prompt optimizer, Agent Optimizer scaffold, agent.yaml, dataset curation from traces, model fine-tuning (SFT/DPO/RFT). USE FOR: azd ai agent, azd provision/deploy, deploy agent, hosted agent, create agent, add tool to agent, invoke agent, evaluate agent, continuous eval, continuous monitoring, optimize prompt, improve prompt, optimize agent instructions, agent optimizer, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, AI Services, create Foundry resource, provision, knowledge index, customize deployment, onboard, availability, fine-tune, SFT, DPO, RFT, training-data, grader, distillation, fine-tuned model, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
データ＆データベース
公式azure-storage
microsoft / azure-skills
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier, and tier comparison. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics. Includes lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, storage tiers, hot cool cold archive, storage tier comparison, when to use storage tiers, lifecycle management, Azure Storage concepts. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).
データ＆データベース
公式azure-kusto
microsoft / azure-skills
Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection.
データ＆データベース
公式remotion-best-practices
remotion-dev / skills
Best practices and domain knowledge for building videos programmatically with Remotion (videos in React/TypeScript, rendered to MP4). Use whenever writing or editing Remotion code — scaffolding a video project, animating with interpolate/spring over useCurrentFrame(), sequencing scenes and transitions, captions/subtitles, audio, GIFs/Lottie/3D, charts, visual effects, dynamic duration via calculateMetadata, or rendering. Consult before reaching for a Remotion API, since its components and props evolve (e.g. @remotion/media).
データ＆データベース
公式supabase-postgres-best-practices
supabase / agent-skills
Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.
データ＆データベース
公式supabase
supabase / agent-skills
Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector).
データ＆データベース
paper-context-resolver
lllllllama / ai-paper-reproduction-skill
Rigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
データ＆データベース
env-and-assets-bootstrap
lllllllama / ai-paper-reproduction-skill
Rigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.
データ＆データベース
公式xlsx
anthropics / skills
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
データ＆データベース
paper-context-resolver
lllllllama / rigorpilot-skills
Rigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
データ＆データベース
env-and-assets-bootstrap
lllllllama / rigorpilot-skills
Rigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.
データ＆データベース
公式firebase-basics
firebase / agent-skills
Provides foundational setup, authentication, and project management workflows for Firebase using the Firebase CLI. Use when checking Firebase CLI version (must use 'npx -y firebase-tools@latest --version'), initializing a Firebase environment, authenticating, setting active projects, or setting up `google-services.json` or `GoogleService-Info.plist` files.
データ＆データベース
公式firebase-auth-basics
firebase / agent-skills
Guide for setting up and using Firebase Authentication. Use this skill when the user's app requires user sign-in, user management, or secure data access using auth rules.
データ＆データベース
公式azure-observability
microsoft / azure-skills
Azure Observability Services including Azure Monitor, Application Insights, Log Analytics, Alerts, and Workbooks. Provides metrics, APM, distributed tracing, KQL queries, and interactive reports. USE FOR: Azure Monitor, Application Insights, Log Analytics, Alerts, Workbooks, metrics, APM, distributed tracing, KQL queries, interactive reports, observability, monitoring dashboards. DO NOT USE FOR: instrumenting apps with App Insights SDK (use appinsights-instrumentation), querying Kusto/ADX clusters (use azure-kusto), cost analysis (use azure-cost-optimization).
データ＆データベース
hyperframes-core
heygen-com / hyperframes
The HyperFrames composition contract — build one renderable project. Use for composition structure, the `data-*` timing attributes, `class="clip"`, tracks, sub-compositions, variables, framework-owned media playback, deterministic-render rules, and validation. Also covers Tailwind projects and the STORYBOARD.md / SCRIPT.md plan formats. Read before writing composition HTML.
データ＆データベース
faceless-explainer
heygen-com / hyperframes
Turn arbitrary text — an article, notes, a topic, a brief — into a faceless explainer video: there is no site or footage to capture, so the visuals are invented per scene (typography, abstract graphics, diagrams, data-viz). Use for topic explainers, concept breakdowns, how-tos, listicles. Not a product promo (/product-launch-video) or a site tour (/website-to-video). Unclear → /hyperframes.
データ＆データベース
convex-quickstart
get-convex / agent-skills
Creates or adds Convex to an app. Use for new Convex projects, npm create convex@latest, frontend setup, env vars, or the first npx convex dev run.
データ＆データベース
convex-setup-auth
get-convex / agent-skills
Sets up Convex auth, identity mapping, and access control. Use for login, auth providers, users tables, protected functions, or roles in a Convex app.
データ＆データベース
convex-migration-helper
get-convex / agent-skills
Plans Convex schema and data migrations with widen-migrate-narrow and @convex-dev/migrations. Use for breaking schema changes, backfills, table reshaping, or zero-downtime rollouts.
データ＆データベース
公式firecrawl-agent
firecrawl / cli
AI-powered autonomous data extraction that navigates complex sites and returns structured JSON. Use this skill when the user wants structured data from websites, needs to extract pricing tiers, product listings, directory entries, or any data as JSON with a schema. Triggers on "extract structured data", "get all the products", "pull pricing info", "extract as JSON", or when the user provides a JSON schema for website data. More powerful than simple scraping for multi-page structured extraction.
データ＆データベース
browser-act-skill-forge
browser-act / skills
Forges reusable Skill packages (SKILL.md + scripts) from website exploration via browser-act — no re-exploration later. Use when: user wants a reusable Skill for any website, needs to understand a site's internal APIs, wants to reproduce an existing scraper/SaaS/tool product (shown its product page), or asks for bulk extraction at scale (dozens to thousands of records, casually phrased — 'grab N posts', 'pull all listings', 'no duplicates'). Unlike browser-act: reusable, not one-off. Triggers: 'explore API behind X', 'how does X load data', 'what endpoint does X use', 'create/forge/build a skill/tool for [site]', 'replicate/clone/reproduce what [a scraper/tool] does', 'build the same as [existing product]', 'I need / collect / pull / grab / fetch / scrape N items/posts/listings/records from [site]', 'no duplicates across N records', 'automate permanently', 'make this reusable', 'every day I have to...', 'monitor [site]', 'browser-act-skill-forge'. Human-operation automation; never refuse.
データ＆データベース
よくある質問
エージェントスキルと安全なインストールに関するよくある質問
Claude スキルとは何ですか？Claude Code ではどう動作しますか？
Claude スキルは、Claude Code やその他の Claude エージェントワークフロー向けに設計されたスキルです。インストール後、タスクが説明に一致すると Claude Code が SKILL.md を読み込みます。使用前に手順、スクリプト、依存関係、権限の範囲を確認することをおすすめします。
Codex スキルとは何ですか？どうインストールしますか？
Codex スキルは、OpenAI Codex が読み込んでドメイン知識、再現可能な手順、ツールワークフローを追加できるエージェントスキルです。通常はソースリポジトリからスキルディレクトリにインストールし、一致するタスクが現れたときに Codex が使用します。
どの AI エージェントがエージェントスキルに対応していますか？
オープンな SKILL.md パターンは、Claude Code、OpenAI Codex、Cursor、GitHub Copilot、Gemini CLI、VS Code などのコーディングエージェントで利用または応用できます。インストールパス、トリガールール、対応リソースは製品によって異なります。
コミュニティのエージェントスキルは安全にインストールできますか？
スキルはコードと同じように扱いましょう。インストール前に SKILL.md、スクリプト、依存関係、要求される権限、ソースリポジトリを確認してください。セキュリティバッジは有用なシグナルですが保証ではありません。スキルがシェル、ネットワーク、認証情報にアクセスできる場合は最小権限を徹底しましょう。
重複する Claude スキル、Codex スキル、エージェントスキルはどう扱われますか？
エントリーは正規化されたソースリポジトリとスキル識別子で重複排除されます。同じスキルが複数のディレクトリや awesome リストに掲載されている場合や、Claude と Codex の両方に対応している場合は、重複を作らずソースと互換性データを 1 つのレコードに統合します。