Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
37.891 de skill-uri din 1.729 de depozite · actualizat acum 12 minute
37.891 de skill-uri
- squirrelsickn33/agentic-awesome-skillsFull-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.TestareFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- ruff-recursive-fixgithub/awesome-copilotRun Ruff checks with optional scope and rule overrides, apply safe and unsafe autofixes iteratively, review each change, and resolve remaining findings with targeted edits or user decisions.RedactareFără avertismente★ 40,4 K↓ —
- vscode-ext-commandsgithub/awesome-copilotGuidelines for contributing commands in VS Code extensions. Indicates naming convention, visibility, localization and other relevant attributes, following VS Code extension development guidelines, libraries and good practicesInginerieFără avertismente★ 40,4 K↓ —
- mcp-security-auditgithub/awesome-copilotAudit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP package-runner dependencies use exact reviewed versions, not bare names, @latest, or ranges - Detecting mutable npm/npx, bunx, pnpm dlx, yarn dlx, and npm exec references in MCP configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]SecuritateFără avertismente★ 40,4 K↓ —
- qdrant-clients-sdkgithub/awesome-copilotQdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.DevOpsFără avertismente★ 40,4 K↓ —
- spring-boot-testinggithub/awesome-copilotExpert Spring Boot 4 testing specialist that selects the best Spring Boot testing techniques for your situation with Junit 6 and AssertJ.TestareFără avertismente★ 40,4 K↓ —
- dataladK-Dense-AI/scientific-agent-skillsRetrieves, versions, and publishes scientific datasets with DataLad and git-annex, and captures computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.ȘtiințăFără avertismente★ 54,4 K↓ —Apare și în 1 alt depozit
- dailysickn33/agentic-awesome-skillsDocumentation and capabilities reference for DailyAlteleFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- google-cloud-slo-alert-configurationgoogle/skillsConfigures Cloud Monitoring PromQL-based Service Level Objective (SLO) alerting policies on Google Cloud for resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting policies.OficialDevOpsFără avertismente★ 21,5 K↓ —
- seo-plansickn33/agentic-awesome-skillsStrategic SEO planning for new or existing websites. Industry-specific templates, competitive analysis, content strategy, and implementation roadmap. Use when user says "SEO plan", "SEO strategy", "content strategy", "site architecture", or "SEO roadmap".MarketingFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- harness-engineeringgithub/awesome-copilotAdopt repository-level harness engineering for coding agents. Use when a user wants to prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.TestareFără avertismente★ 40,4 K↓ —
- google-cloud-recipe-authgoogle/skillsProvides expert guidance on Identity and Access Management (IAM) and authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.OficialAlteleFără avertismente★ 21,5 K↓ —Apare și în 1 alt depozit
- azure-role-selectorgithub/awesome-copilotWhen user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.DevOpsFără avertismente★ 40,4 K↓ —
- verify-agent-actiongithub/awesome-copilotReview a proposed AI-agent action or human-approval packet before execution. Use when an agent wants to run a consequential tool, command, deployment, message, purchase, credential operation, or data mutation; when checking whether approval still matches the exact action; or when auditing action evidence for forged results, parameter swaps, replay, correlated reviewers, missing evidence, expiry, or stale monitoring. Produce an evidence-based review only—never execute or authorize the action.DevOpsFără avertismente★ 40,4 K↓ —
- code-reviewgithub/awesome-copilotReview pull requests for repository fit, meaningful value, trustworthy provenance, differentiation, and maintainability in awesome-copilot.InginerieFără avertismente★ 40,4 K↓ —
- huggingface-besthuggingface/skillsUse when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.OficialPlanificareFără avertismente★ 11,2 K↓ —
- huashu-designalchaincyf/huashu-design花叔Design——用HTML做高保真原型、幻灯片、动画、可视化与专家评审。任何新设计100%先出三个方向初稿给用户选（指定风格/品牌也不豁免），选定后才执行。触发词：做原型、PPT、幻灯片、动画、设计风格、评审、做个HTML页面、UI mockup、导出MP4/GIF、做个好看的。生产级Web App/需后端的系统不适用。DesignFără avertismente★ 26,1 K↓ —Apare și în 1 alt depozit
- gemini-api-devgoogle-gemini/gemini-skillsUse this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, speech generation (TTS), voice design, voice replication, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best practices for Gemini models and agents in Python and TypeScript.OficialInginerieFără avertismente★ 4,3 K↓ —
- hf-memhuggingface/skillsHugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face HubOficialInginerieFără avertismente★ 11,2 K↓ —Apare și în 1 alt depozit
- huggingface-lora-space-builderhuggingface/skillsBuild and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.OficialDesignFără avertismente★ 11,2 K↓ —
- hf-cloud-sagemaker-deployment-plannerhuggingface/skillsPlan 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.OficialDevOpsFără avertismente★ 11,2 K↓ —
- gemini-live-api-devgoogle-gemini/gemini-skillsUse this skill when building real-time, bidirectional streaming applications with the Gemini Live API, or migrating legacy Live models (2.0/2.5/3.1) to Gemini 3.8 Live. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), background reasoning (extended thinking), asynchronous function calling, session management, ephemeral tokens, live transcription, and live translation. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript).OficialInginerieFără avertismente★ 4,3 K↓ —
- transformers-jshuggingface/skillsUse Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.OficialMediaFără avertismente★ 11,2 K↓ —Apare și în 1 alt depozit
- gws-calendargoogleworkspace/cliGoogle Calendar: Manage calendars and events.ProductivitateFără avertismente★ 31,8 K↓ —
preference-optimization
wshobson/agents
InginerieActualizat ieri
De la autor
Align a fine-tuned model with preference data using DPO, ORPO, KTO, or SimPO. Use when preference pairs or thumbs-up/down feedback exist, when choosing between preference-optimization methods, or when a DPO run needs hyperparameters or debugging.
Instalare
npx skills add wshobson/agents --skill preference-optimization -a claude-code
Se instalează în .claude/skills/preference-optimization/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 95
Securitate100
Proveniență95
Întreținere100
Licență100
Adopție71
Fișiere (2)
- SKILL.md
- references/method-configs.md