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fedi.software

에이전트 스킬

skills.sh 디렉터리에 있는 Claude Code, Codex, Cursor 등 에이전트용 스킬: 설치 수, 보안 감사 상태, 스킬을 추가하는 명령어.

스킬은 특정 에이전트에 묶여 있지 않습니다. npx skills add는 지원되는 어떤 에이전트에도 설치합니다. -a 없이 실행하면 CLI가 컴퓨터의 에이전트를 찾아 어디에 추가할지 묻습니다.

업데이트 · 출처: skills.sh

표시: 77 · 검색 결과: 77개 · 디렉터리 전체 10,000개 중

  • firebase-firestore firebase/agent-skills

    Sets up, manages, queries, and configures Cloud Firestore databases (Standard/Enterprise edition), including data modeling, security rules, indexes, and SDK integrations (Web, Python, iOS, Android, Flutter). Use when creating/listing Firestore databases, defining data models/indexes, writing SDK queries, or integrating Firestore SDKs. For authoring or modifying Firestore Security Rules (firestore.rules), delegate to the firestore-rules-author subagent if subagent delegation is available, or use firestore-rules-creation otherwise. Don't use for Firebase Hosting, Data Connect, Auth, Storage/GCS, Crashlytics, Functions, or BigQuery.

    124,678 경고
  • python-executor 101-skills/superpowers

    Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

    85,117 경고
  • python-executor qu-skills/superpowers

    Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

    45,639 경고
  • python-executor magentosh/superpowers

    Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

    36,366 경고
  • python-executor skills-shell/superpowers

    Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

    27,594 경고
  • python-executor its-a-skill-issue/superpowers

    Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

    26,600 경고
  • python-executor bankai-skills/superpowers

    Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

    24,721 경고
  • nature-figure yuan1z0825/nature-skills

    Create, revise, audit, and export manuscript scientific figures in Python or R. Use for 论文配图、科研绘图、多面板图 and submission-ready plots, or explicitly requested AI-generated graphical abstracts and mechanism schematics. Not for interactive dashboards, data cleaning, or statistics-only analysis.

    16,515 경고
  • uv-package-manager wshobson/agents

    Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.

    14,321 경고
  • huawei-cloud-iam-query huaweicloud/huaweicloud-skills

    Queries Huawei Cloud identity and access management resources (IAM) via read-only Python SDK. Covers users, groups, policies, agencies, AK/SK, MFA devices, login/password/ACL policies, security compliance, and account quotas. No write operations. Use this skill when the user needs to query IAM identity info, check policies/permissions, view agency details, or inspect AK/SK/MFA status. Triggers: IAM, 用户, 用户组, 策略, 委托, 权限, AK/SK, MFA, 密码策略, 安全合规, 身份查询, 身份认证, identity, policy, agency.

    13,713 경고
  • huawei-cloud-obs-website-host huaweicloud/huaweicloud-skills

    Configure Huawei Cloud OBS static website hosting with Python SDK and a custom domain. Use when the user needs to enable or repair OBS website hosting, set index or error pages, expose an existing bucket for public website access through a custom domain, or connect that domain through Huawei Cloud DNS when Huawei manages the zone. Triggers include OBS static website hosting, website endpoint, index page, error page, public-read bucket website access, custom domain CNAME, Huawei Cloud DNS, setBucketWebsite. 中文触发词包括:OBS 静态网站托管、网站托管、自定义域名解析。

    13,694 경고
  • pdf openai/skills

    Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.

    12,979 경고
  • pytest-coverage github/awesome-copilot

    Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.

    12,697 경고
  • django-patterns affaan-m/ecc

    Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps. Use when building or reviewing Django apps, DRF APIs, ORM queries, or caching.

    11,838 경고
  • python-observability wshobson/agents

    Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.

    10,964 경고
  • python-mcp-server-generator github/awesome-copilot

    Generate a complete MCP server project in Python with tools, resources, and proper configuration

    10,357 경고
  • dataverse-python-production-code github/awesome-copilot

    Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices

    9,790 경고
  • dataverse-python-advanced-patterns github/awesome-copilot

    Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.

    9,201 경고
  • comment-code-generate-a-tutorial github/awesome-copilot

    Transform this Python script into a polished, beginner-friendly project by refactoring the code, adding clear instructional comments, and generating a complete markdown tutorial.

    8,852 경고
  • bigquery-pipeline-audit github/awesome-copilot

    Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations.

    8,805 경고
  • dataverse-python-quickstart github/awesome-copilot

    Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.

    8,732 경고
  • dataverse-python-usecase-builder github/awesome-copilot

    Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations

    8,700 경고
  • videodb affaan-m/ecc

    Ingest, index, search, edit, and monitor video and audio with the VideoDB Python SDK — upload from files, URLs, or RTSP feeds, build spoken and scene indexes with timestamped search and playable clips, transcode and reframe, do timeline edits (subtitles, overlays, dubbing), and run real-time alerts on live streams or desktop capture. Use when working with video search, transcription, clipping, transcoding, streaming, or live video alerts.

    8,656 경고
  • atheris trailofbits/skills

    Sets up and runs Atheris, the coverage-guided Python fuzzer built on libFuzzer. Covers TestOneInput harnesses, FuzzedDataProvider, instrumenting both pure Python and native C extensions, and running under AddressSanitizer. Use when fuzzing a Python package, hunting memory corruption in a Python C extension, or choosing between Atheris and Hypothesis for a Python target.

    4,812 경고
  • n8n-code-python czlonkowski/n8n-skills

    Write Python in n8n Code nodes (native Python, `language` pythonNative, n8n 2.x). Use when the user explicitly wants Python in a Code node, when migrating old Pyodide/"Python (Beta)" code that used _input/_json/_node/_now, or when a Python Code node fails with NameError, "Security violations detected", "Import of standard library module … is disallowed", "__build_class__ not found", "A 'json' property isn't a dictionary", or "Python runner unavailable". Covers the only two variables (_items/_item), dict-only access, imports blocked by default, the sandbox's denied builtins, accepted return shapes, and how errors interact with onError. JavaScript is the default for Code nodes — native Python has no n8n helpers and, by default, no imports. EXCEPTION — for Python in the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode), use the n8n-code-tool skill instead (input is _query, return must be a string).

    4,509 경고
  • web-scraping mindrally/skills

    Expert in web scraping and data extraction with Python tools

    4,442 경고
  • flowstudio-power-automate-mcp github/awesome-copilot

    Foundation skill for Power Automate via FlowStudio MCP — auth setup, the reusable MCP helper (Python + Node.js), tool discovery via `list_skills` / `tool_search`, and oversized-response handling. Load this skill first when connecting an agent to Power Automate. For specialized workflows, load `flowstudio-power-automate-build`, `flowstudio-power-automate-debug`, `flowstudio-power-automate-monitoring` (Pro+), or `flowstudio-power-automate-governance` (Pro+) — each contains the workflow narrative, this skill provides the plumbing they all rely on. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app

    4,233 경고
  • langgraph-python-quickstart langchain-ai/langchain-skills

    Scaffold a minimal local LangGraph agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangGraph agent locally.

    4,096 경고
  • langchain-python-quickstart langchain-ai/langchain-skills

    Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.

    3,971 경고
  • deepagents-python-quickstart langchain-ai/langchain-skills

    Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.

    3,949 경고
  • yfinance-data himself65/finance-skills

    Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.

    3,609 경고
  • generating-python-installer affaan-m/ecc

    Commercial-grade Python installer expert for Windows: Nuitka extreme compilation, dist slimming, DLL footprint analysis, and Inno Setup packaging to ship the smallest, fastest installers. Use when a Python app must ship as a minimal, fast-starting Windows installer; not for basic script-to-exe conversion. 中文触发:Nuitka 极限优化、Python 商业打包、极限编译 Python、dist 瘦身、DLL 分析、最小安装包、最快启动、商业级打包风格

    3,565 경고
  • aws-lambda-python-integration giuseppe-trisciuoglio/developer-kit

    Provides AWS Lambda integration patterns for Python with cold start optimization. Use when deploying Python functions to AWS Lambda, choosing between AWS Chalice and raw Python approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless Python applications. Triggers include "create lambda python", "deploy python lambda", "chalice lambda aws", "python lambda cold start", "aws lambda python performance", "python serverless framework".

    3,446 경고
  • open-source browser-use/browser-use

    Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browser_use, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle hooks, MCP server setup, or monitoring/observability with Laminar or OpenLIT. Also trigger for questions about browser-use installation, prompting strategies, or sensitive data handling. Do NOT use this for Cloud API/SDK usage or pricing — use the cloud skill instead. Do NOT use this for directly automating a browser via CLI commands — use the browser-use skill instead.

    3,335 경고
  • office-automation texiaoyao/office-automation-skill

    自动化处理 Word 和 Excel 文件。使用 Python 脚本读取、写入、格式化文档和表格。支持批量处理、模板填充、数据提取和格式转换。

    2,986 경고
  • accelerated-computing-cudf nvidia/skills

    Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.

    2,950 경고
  • agentmail agentmail-to/agentmail-skills

    Build with the AgentMail TypeScript or Python SDK for inbox, message, thread, draft, attachment, domain, allow/block list, pod, webhook, and WebSocket workflows, including programmatic agent sign-up, domain/DNS administration, and deliverability triage (bounces, spam, blocked mail). Use when implementing or reviewing AgentMail API code; do not use for direct mailbox operations, CLI usage, MCP setup, or framework-toolkit integration.

    2,848 경고
  • observability-edot-python-instrument elastic/agent-skills

    2,730 경고
  • django-perf-review getsentry/skills

    Django performance code review. Use when asked to "review Django performance", "find N+1 queries", "optimize Django", "check queryset performance", "database performance", "Django ORM issues", or audit Django code for performance problems.

    2,715 경고
  • observability-edot-python-migrate elastic/agent-skills

    2,695 경고
  • cuopt-install nvidia/skills

    Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.

    2,462 경고
  • sentry-python-sdk getsentry/sentry-for-ai

    Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.

    2,453 경고
  • django-access-review getsentry/skills

    Django access control and IDOR security review. Use when reviewing Django views, DRF viewsets, ORM queries, or any Python/Django code handling user authorization. Trigger keywords: "IDOR", "access control", "authorization", "Django permissions", "object permissions", "tenant isolation", "broken access".

    2,446 경고
  • pulumi-best-practices pulumi/agent-skills

    Load when the user is writing, reviewing, or debugging Pulumi TypeScript/Python programs; asks about Output<T> or apply() usage; wants to create ComponentResource classes; needs to refactor resources without destroying them (aliases); is setting up secrets or config; or is configuring a pulumi preview/up CI workflow. Also load for questions about resource dependency order, parent/child resource relationships, or pulumi.interpolate.

    2,269 경고
  • backend-development mrgoonie/claudekit-skills

    Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

    2,214 경고
  • pydantic-ai-harness pydantic/skills

    Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness -- Code Mode (collapse many tool calls into one sandboxed Python execution), a filesystem and shell, sub-agents, planning, context compaction, and more. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want first-party filesystem/shell/sub-agent/planning/compaction capabilities for a Pydantic AI agent, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.

    2,190 경고
  • python-backend jiatastic/open-python-skills

    Python backend development expertise for FastAPI, security patterns, database operations, Upstash integrations, and code quality. Use when: (1) Building REST APIs with FastAPI, (2) Implementing JWT/OAuth2 authentication, (3) Setting up SQLAlchemy/async databases, (4) Integrating Redis/Upstash caching, (5) Refactoring AI-generated Python code (deslopification), (6) Designing API patterns, or (7) Optimizing backend performance.

    2,139 경고
  • blender-mcp vladmdgolam/agent-skills

    Blender MCP expert for scene inspection, Python scripting, GLTF export, and material/animation extraction. Activate when: (1) using Blender MCP tools (get_scene_info, execute_python, screenshot, etc.), (2) writing Blender Python scripts for extraction or manipulation, (3) exporting scenes to GLTF/GLB for web (Three.js, R3F), (4) debugging material or texture export losses, (5) optimizing GLB files with gltf-transform, (6) using asset integrations (PolyHaven, Sketchfab, Hyper3D Rodin, Hunyuan3D). Covers critical export gotchas, material mapping survival, texture optimization pipeline, headless CLI patterns, and known failure modes.

    2,102 경고
  • tigris-image-optimization tigrisdata/skills

    Use when resizing images, generating thumbnails, serving responsive images, or optimizing image delivery with Tigris — covers Next.js, Remix, Rails, Django, Laravel, Express

    2,075 경고
  • csv-data-summarizer coffeefuelbump/csv-data-summarizer-claude-skill

    Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.

    2,074 경고
  • harvard-art-museums-etl-analytics reason-machines/data-skills

    Build ETL pipelines and analytics dashboards using Harvard Art Museums API with Python, SQL, and Streamlit

    2,014 경고
  • jianying-editor luoluoluo22/jianying-editor-skill

    剪映 (JianYing) AI自动化剪辑的高级封装 API (JyWrapper),提供开箱即用的 Python 接口,支持录屏、素材导入、字幕生成、Web 动效合成及项目导出。全面适配 MacOS (Apple Silicon/Intel) 与 Windows,支持 v5.9+ (draft_info.json) 架构、工程自修复、智能配音字幕及录屏变焦。

    1,999 경고
  • harvard-artifacts-data-engineering-analytics reason-machines/data-skills

    Build end-to-end ETL pipelines and analytics dashboards using the Harvard Art Museums API with Python, SQL, and Streamlit

    1,998 경고
  • harvard-art-museum-data-pipeline reason-machines/data-skills

    Build ETL pipelines and analytics dashboards using the Harvard Art Museums API with Streamlit, MySQL, and Python

    1,978 경고
  • harvard-artifacts-collection-etl-analytics reason-machines/data-skills

    Build ETL pipelines and analytics dashboards for Harvard Art Museums API data using Python, SQL, and Streamlit

    1,940 경고
  • microsoft-agent-framework github/awesome-copilot

    Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.

    1,933 경고
  • ccxt-python ccxt/ccxt

    CCXT cryptocurrency exchange library for Python developers. Covers both REST API (standard) and WebSocket API (real-time). Helps install CCXT, connect to exchanges, fetch market data, place orders, stream live tickers/orderbooks, handle authentication, and manage errors in Python. Use when working with crypto exchanges in Python projects, trading bots, data analysis, or portfolio management. Supports both sync and async (asyncio) usage.

    1,910 경고
  • harvard-artifacts-etl-streamlit-analytics reason-machines/data-skills

    Build ETL pipelines and analytics dashboards using Harvard Art Museums API data with Python, SQL, and Streamlit

    1,891 경고
  • statsmodels k-dense-ai/scientific-agent-skills

    Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.

    1,880 경고
  • holoscan-install-wheel nvidia/skills

    Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.

    1,789 경고
  • sympy k-dense-ai/scientific-agent-skills

    Use when you need exact symbolic math in Python — algebra, calculus, equation solving, symbolic linear algebra, or code generation via lambdify/LaTeX. Prefer NumPy or SciPy when floating-point approximations are sufficient.

    1,786 경고
  • harvard-art-museums-etl-pipeline reason-machines/data-skills

    Build ETL pipelines and analytics dashboards using Harvard Art Museums API with Python, SQL, and Streamlit

    1,779 경고
  • dask k-dense-ai/scientific-agent-skills

    Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

    1,775 경고
  • benchling-integration k-dense-ai/scientific-agent-skills

    Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.

    1,695 경고
  • adaptyv k-dense-ai/scientific-agent-skills

    How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

    1,690 경고
  • semantic-kernel github/awesome-copilot

    Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.

    1,681 경고
  • cuopt-numerical-optimization-api-python nvidia/skills

    1,676 경고
  • rowan k-dense-ai/scientific-agent-skills

    Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

    1,662 경고
  • tilegym-cutile-python nvidia/skills

    Expert cuTile programming assistant. Write high-performance GPU kernels using cuTile's tile-based programming model with proper validation and optimization. Supports deep agent orchestration for complex multi-kernel tasks.

    1,630 경고
  • markitdown julianobarbosa/claude-code-skills

    Guide for using Microsoft MarkItDown - a Python utility for converting files to Markdown. Use when converting PDF, Word, PowerPoint, Excel, images, audio, HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs, Jupyter notebooks, RSS feeds, or Wikipedia pages to Markdown format. Also use for document processing pipelines, LLM preprocessing, or text extraction tasks.

    1,603 경고
  • context7 netresearch/context7-skill

    Use when looking up library documentation, API references, framework patterns, or code examples for ANY library (React, Next.js, Vue, Django, Laravel, etc.) and the Context7 MCP server is unavailable or not configured. Fetches the same current docs directly via the Context7 REST API as a fallback. Triggers on: how to use library, API docs, framework pattern, import usage, library example.

    1,584 경고
  • data-analysis-jupyter mindrally/skills

    Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.

    1,488 경고
  • tilegym-converting-cutile-to-julia nvidia/skills

    Converts cuTile Python GPU kernels (@ct.kernel) to cuTile.jl Julia equivalents. Handles kernel syntax translation, 0-indexed to 1-indexed conversion, broadcasting differences, memory layout (row-major to column-major), type system mapping, and launch API differences. Use when converting, porting, or translating cuTile Python kernels to Julia cuTile.jl, or debugging/optimizing existing Julia cuTile translations.

    1,473 경고
  • odoo-18 unclecatvn/agent-skills

    Odoo 18 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 18 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/list/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code. Includes CSS/SCSS asset authoring and review for Odoo addons.

    1,420 경고
  • flask-python mindrally/skills

    Guidelines for Flask Python development with best practices for blueprints, RESTful APIs, and application factories.

    1,376 경고
  • mcp-builder jezweb/claude-skills

    Build MCP servers in Python with FastMCP. Define tools / resources / prompts, build the server, test locally, deploy to FastMCP Cloud or Docker. Use whenever the user mentions building an MCP server, exposing tools to LLMs, FastMCP, building a Claude integration, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.

    1,374 경고
  • 1,269 경고

설명은 작성자가 직접 쓴 영어 원문입니다. 설치하기 전에 저장소에서 스킬 코드를 확인하세요.

에이전트 스킬이란

스킬은 SKILL.md 파일과 필요하면 스크립트를 담은 폴더로, 작업 내용이 맞을 때 에이전트가 불러와 씁니다. 이 페이지에서는 skills.sh 디렉터리에 있는 Claude Code, Codex, Cursor 등 에이전트용 스킬을 볼 수 있습니다. 이름, 작성자와 저장소, 설치 수, 보안 감사 상태, 스킬을 추가하는 명령(「명령어 복사」 버튼)이 표시됩니다.

목록의 구조

  • 설치 수 상위 10,000개를 매일 동기화합니다.
  • 「인기 급상승」은 최근 7일 동안 늘어난 설치 수 순서입니다.
  • 주제와 에이전트로 거르고 검색할 수 있으며, 한 번에 최대 100개가 보입니다.
  • 설명은 작성자가 쓴 영어 그대로이며 번역하지 않습니다.

감사 상태 읽는 법

감사 상태는 skills.sh가 공개한 감사 결과를 바탕으로 「통과」, 「경고」, 「실패」, 「감사 안 됨」 네 가지로 보여 줍니다. 다만 「통과」라도 안전이 보장되는 것은 아닙니다. 스킬은 에이전트를 통해 여러분의 PC에서 돌아가므로 설치 전에 GitHub 저장소에서 코드를 읽어 보십시오. 설치 수는 skills.sh가 센 값입니다.

쓰기 시작하려면

목적에 가까운 주제로 거르고 감사 상태와 저장소를 확인했다면, 「명령어 복사」로 명령을 받아 쓰는 에이전트에서 실행합니다. 에이전트 자체를 고르는 단계라면 코딩 에이전트 페이지부터 보십시오.