Ajan becerileri
skills.sh dizininden Claude Code, Codex, Cursor ve diğer ajanlar için beceriler: kurulum sayıları, güvenlik denetimi durumu ve beceriyi ekleme komutu.
Bir skill tek bir ajana bağlı değildir: npx skills add onu desteklenen herhangi bir ajana kurar. -a olmadan CLI bilgisayarınızdaki ajanları bulur ve nereye ekleneceğini sorar.
Güncellendi · Kaynaklar: skills.sh
Gösterilen: 77 · bulunan: 77 · dizindeki 10.000 beceriden
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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.
125.813 Uyarılar -
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
87.455 Uyarılar -
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
48.111 Uyarılar -
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
41.741 Uyarılar -
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
30.019 Uyarılar -
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
28.949 Uyarılar -
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
27.161 Uyarılar -
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.
16.698 Uyarılar -
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.
14.449 Uyarılar -
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.
14.248 Uyarılar -
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。
14.229 Uyarılar -
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.
13.022 Uyarılar -
pytest-coverage github/awesome-copilot
Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.
12.707 Uyarılar -
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.
11.882 Uyarılar -
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.
11.037 Uyarılar -
python-mcp-server-generator github/awesome-copilot
Generate a complete MCP server project in Python with tools, resources, and proper configuration
10.363 Uyarılar -
dataverse-python-production-code github/awesome-copilot
Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices
9.791 Uyarılar -
dataverse-python-advanced-patterns github/awesome-copilot
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
9.202 Uyarılar -
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 Uyarılar -
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 Uyarılar -
dataverse-python-quickstart github/awesome-copilot
Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.
8.732 Uyarılar -
dataverse-python-usecase-builder github/awesome-copilot
Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations
8.700 Uyarılar -
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.
8.684 Uyarılar -
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.
4.846 Uyarılar -
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).
4.532 Uyarılar -
web-scraping mindrally/skills
Expert in web scraping and data extraction with Python tools
4.444 Uyarılar -
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
4.235 Uyarılar -
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.
4.230 Uyarılar -
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.
4.099 Uyarılar -
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.
4.079 Uyarılar -
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.
3.618 Uyarılar -
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
3.592 Uyarılar -
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".
3.461 Uyarılar -
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.
3.359 Uyarılar -
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 Uyarılar -
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.
2.958 Uyarılar -
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.
2.864 Uyarılar -
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.
2.731 Uyarılar -
observability-edot-python-instrument elastic/agent-skills
2.730 Uyarılar -
observability-edot-python-migrate elastic/agent-skills
2.695 Uyarılar -
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.
2.468 Uyarılar -
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.
2.467 Uyarılar -
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".
2.462 Uyarılar -
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.
2.316 Uyarılar -
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.
2.239 Uyarılar -
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.
2.220 Uyarılar -
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
2.171 Uyarılar -
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 Uyarılar -
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.
2.122 Uyarılar -
csv-data-summarizer coffeefuelbump/csv-data-summarizer-claude-skill
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
2.079 Uyarılar -
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。
2.020 Uyarılar -
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 Uyarılar -
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 Uyarılar -
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 Uyarılar -
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 Uyarılar -
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 Uyarılar -
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.
1.925 Uyarılar -
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.
1.902 Uyarılar -
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 Uyarılar -
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.
1.805 Uyarılar -
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.
1.794 Uyarılar -
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.
1.790 Uyarılar -
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 Uyarılar -
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.
1.714 Uyarılar -
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`.
1.709 Uyarılar -
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.
1.682 Uyarılar -
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.
1.680 Uyarılar -
cuopt-numerical-optimization-api-python nvidia/skills
1.676 Uyarılar -
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.
1.633 Uyarılar -
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.
1.622 Uyarılar -
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 Uyarılar -
data-analysis-jupyter mindrally/skills
Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
1.490 Uyarılar -
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.
1.474 Uyarılar -
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.
1.426 Uyarılar -
flask-python mindrally/skills
Guidelines for Flask Python development with best practices for blueprints, RESTful APIs, and application factories.
1.388 Uyarılar -
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.
1.378 Uyarılar -
pytest bobmatnyc/claude-mpm-skills
pytest - Python's most powerful testing framework with fixtures, parametrization, plugins, and framework integration for FastAPI, Django, Flask
1.274 Uyarılar
Açıklamalar yazarların kendisine aittir ve İngilizcedir. Bir beceriyi kurmadan önce deposundaki kodunu okuyun.
Beceri (skill), bir SKILL.md dosyası ve gerekirse birkaç betik içeren bir klasördür. Verdiğiniz görev becerinin tarif ettiği işe uyduğunda ajan onu yükler: örneğin belirli bir çatıyla nasıl çalışılacağı, belgelerin nasıl yazılacağı ya da bir dağıtımın nasıl hazırlanacağı. Böylece ajanınızın bildiklerini, her sohbette yeniden anlatmadan genişletirsiniz.
Dizinin kaynağı
Beceriler Claude Code, Codex, Cursor ve diğer ajanlar için bir dizin olan skills.sh'den gelir. En çok kurulan 10.000 beceriyi her gün eşitleriz. Her kayıtta ad, yazar ve depo, kurulum sayısı, güvenlik denetimi durumu ve beceriyi ekleme komutu bulunur; «Komutu kopyala» düğmesiyle alırsınız. Açıklamalar yazarlarına aittir, İngilizcedir ve çevrilmez; her becerinin kodu kayıttan bağlantı verilen GitHub deposundadır.
Doğru beceriyi bulmanın adımları
- Sekmeyi seçin. «En çok kurulanlar» toplam kuruluma, «Yükselenler» son 7 günde kazanılan kuruluma göre sıralar.
- Konuya göre daraltın. Frontend, backend, DevOps, veritabanları, güvenlik, belgeler ve diğer konular var.
- Ajanınızı seçin. Yalnızca kullandığınız ajanla uyumlu becerileri görün.
- Arayın. Ad ya da açıklamaya göre arama kutusunu kullanın.
Her görünümde en fazla 100 beceri gösterilir; belirli bir şey arıyorsanız filtrelerle daraltın.
Güvenlik denetimi
Durumlar skills.sh'nin yayımladığı denetimlerden gelir: «Geçti», «Uyarılar», «Başarısız» ve «Denetlenmedi». Geçmiş bir denetim garanti değildir. Bir beceri, ajanın bilgisayarınızda çalıştıracağı betikler içerebilir; kurmadan önce depodaki kodu okuyun, özellikle ağa ya da dosyalarınıza erişim istiyorsa. Kurulum sayıları da skills.sh tarafından tutulur: popülerliği gösterir, kaliteyi ya da güvenliği değil.
Diğer bölümlerle ilişkisi
Beceriler bir ajanın içinde çalışır; önce bir ajan gerekir, onları kodlama ajanları sayfasında bulursunuz. Ajanın başarısı da kullandığı modele bağlıdır; bunu kodlama ve ajanlar sıralamaları gösterir. İyi bir beceri zayıf bir modeli güçlendirmez, ama tekrarlanan talimatlardan kurtarır ve ajanın projenizin kurallarına uymasını sağlar.