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.
31.266 de skill-uri din 1.362 de depozite · actualizat acum 9 minute
31.266 de skill-uri
- gguf-quantizationOrchestra-Research/AI-Research-SKILLsGGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.DevOpsFără avertismente★ 13,9 K↓ —
- clipOrchestra-Research/AI-Research-SKILLsOpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.MediaFără avertismente★ 13,9 K↓ —
- peft-fine-tuningOrchestra-Research/AI-Research-SKILLsParameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.ProductivitateFără avertismente★ 13,9 K↓ —
- awq-quantizationOrchestra-Research/AI-Research-SKILLsActivation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.DevOpsFără avertismente★ 13,9 K↓ —
- declarative-agent-developermicrosoft/skillsCreate, build, deploy, and localize declarative agents for M365 Copilot and Teams. USE THIS SKILL for ANY task involving a declarative agent — including localization, scaffolding, editing manifests, adding capabilities, and deploying. Localization requires tokenized manifests and language files that only this skill knows how to produce. Triggers: "create agent", "create a declarative agent", "new declarative agent", "scaffold an agent", "new agent project", "add a capability", "add a plugin", "configure my agent", "deploy my agent", "fix my agent manifest", "edit my agent", "localize my agent", "add localization", "translate my agent", "multi-language agent", "add an API plugin", "add an MCP plugin", "add OAuth to my plugin", "review instructions", "improve instructions", "fix my instructions"OficialDevOpsFără avertismente★ 3,1 K↓ —
- golden-html-multiyusufkaraaslan/Skill_SeekersUse when testing the multi-file html buildTestareFără avertismente★ 15,2 K↓ —
- golden-jupyter-kwyusufkaraaslan/Skill_SeekersUse when testing the golden_jupyter_kw golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-chat-emptyyusufkaraaslan/Skill_SeekersUse when testing the golden_chat_empty golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-man-singleyusufkaraaslan/Skill_SeekersUse when testing the man golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-pptx-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationDocumenteFără avertismente★ 15,2 K↓ —
- golden-rss-emptyyusufkaraaslan/Skill_SeekersUse when testing the empty rss golden buildTestareFără avertismente★ 15,2 K↓ —
- evolving-ai-agentsOrchestra-Research/AI-Research-SKILLsProvides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.AlteleFără avertismente★ 13,9 K↓ —
- azure-resource-manager-playwright-dotnetmicrosoft/skillsAzure Resource Manager SDK for Microsoft Playwright Testing in .NET. Use for MANAGEMENT PLANE operations: creating/managing Playwright Testing workspaces, checking name availability, and managing workspace quotas via Azure Resource Manager. NOT for running Playwright tests - use Azure.Developer.MicrosoftPlaywrightTesting.NUnit for that. Triggers: "Playwright workspace", "create Playwright Testing workspace", "manage Playwright resources", "ARM Playwright", "PlaywrightWorkspaceResource", "provision Playwright Testing".OficialTestareFără avertismente★ 3,1 K↓ —
- golden-man-kwyusufkaraaslan/Skill_SeekersUse when testing the man golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-pdf-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationDocumenteFără avertismente★ 15,2 K↓ —
- golden-epub-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationTestareFără avertismente★ 15,2 K↓ —
- golden-wordyusufkaraaslan/Skill_SeekersUse when testing the word golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-html-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationTestareFără avertismente★ 15,2 K↓ —
- golden-epubyusufkaraaslan/Skill_SeekersUse when testing the epub golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-htmlyusufkaraaslan/Skill_SeekersUse when testing the html golden buildTestareFără avertismente★ 15,2 K↓ —
- golden-pptxyusufkaraaslan/Skill_SeekersUse when testing the pptx golden buildDocumenteFără avertismente★ 15,2 K↓ —
- gptqOrchestra-Research/AI-Research-SKILLsPost-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.DevOpsFără avertismente★ 13,9 K↓ —
- workers-profilingcloudflare/skillsProfile or debug CPU usage and memory allocation in deployed Cloudflare Workers and Durable Objects. Then use this information to optimize your code.OficialDevOpsFără avertismente★ 3,2 K↓ —
- saveAgriciDaniel/claude-obsidianSave a user-selected answer, decision, insight, or session summary into an Obsidian vault as one reviewed transaction. Use only when the user explicitly asks to preserve specific conversation content, not when they supply a file or URL to ingest. Triggers: /save, save this, save that answer, file this conversation, save this analysis, keep this insight, preserve this chat result.PlanificareFără avertismente★ 15,8 K↓ —
simpo-training
Orchestra-Research/AI-Research-SKILLs
AlteleActualizat 11 oct. 2026
De la autor
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
Instalare
npx skills add Orchestra-Research/AI-Research-SKILLs --skill simpo-training -a claude-code
Se instalează în .claude/skills/simpo-training/ · 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 instrucțiuniFolosește rețeauaLicență: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 93
Securitate100
Proveniență90
Întreținere100
Licență100
Adopție65
Fișiere (4)
- SKILL.md
- references/datasets.md
- references/hyperparameters.md
- references/loss-functions.md