AGENT SKILLS · ミッション装備
実際に使われている Agent Skills
公開リポジトリの検証済み Skills を比較し、機能、内容、導入状況、出典を確認してから追加できます。
- 掲載範囲
- 検証済み
- Skills
- 21,476
- リポジトリ
- 3293
- 最終同期
- 2026/10/22
guyronnenvideo-download
Download video and audio from YouTube and 1000+ sites using yt-dlp. No API keys needed. Use when: (1) Downloading a video from YouTube or other sites, (2) Extracting audio from a video URL, (3) Downloading subtitles/captions from a video, (4) Getting video metadata without downloading.
- 導入数
- 2
- GitHub Stars
- 2
- 更新日
- 4月12日
guyronnenvideo-edit
Edit videos locally using ffmpeg. Trim, concat, resize, speed, overlay, extract audio, compress, and convert. Use when: (1) Trimming or cutting video segments, (2) Concatenating multiple clips, (3) Resizing video for social platforms, (4) Extracting or replacing audio, (5) Compressing video, (6) Converting video formats, (7) Getting video info.
- 導入数
- 2
- GitHub Stars
- 2
- 更新日
- 4月12日
guyronnenvideo-translate
Translate and dub existing videos into multiple languages using HeyGen. Use when: (1) Translating a video into another language, (2) Dubbing video content with lip-sync, (3) Creating multi-language versions of existing videos, (4) Audio-only translation without lip-sync, (5) Working with HeyGen's /v2/videotranslate endpoint.
- 導入数
- 2
- GitHub Stars
- 2
- 更新日
- 4月12日
guyronnenvideo-understand
Understand video content locally using ffmpeg frame extraction and Whisper transcription. No API keys needed. Use when: (1) Understanding what a video contains, (2) Transcribing video audio locally, (3) Extracting key frames for visual analysis, (4) Getting video content without API keys.
- 導入数
- 2
- GitHub Stars
- 2
- 更新日
- 4月12日
guyronnenvisual-style
Create, extract, and apply portable visual design systems via visual-style.md files. Use when: (1) Creating a visual-style.md design system from scratch, (2) Extracting a visual style from a website URL, video, or PDF brand guide, (3) Applying a visual style to HeyGen videos, HTML slides, Figma, or paper.design, (4) Browsing the gallery of pre-built visual styles (Swiss, Saul Bass, Game Boy, etc.), (5) User mentions "visual style", "design system", "brand style", or "style guide", (6) Styling a
- 導入数
- 2
- GitHub Stars
- 2
- 更新日
- 4月12日
guyronnenweb-design-guidelines
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".
- 導入数
- 2
- GitHub Stars
- 2
- 更新日
- 4月12日
orchestra-researchara-compiler
Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchara-rigor-reviewer
Performs ARA Seal Level 2 semantic epistemic review on Agent-Native Research Artifacts, scoring six dimensions (evidence relevance, falsifiability, scope calibration, argument coherence, exploration integrity, methodological rigor) and producing a constructive, severity-ranked report with a Strong Accept-to-Reject recommendation. Use after Level 1 structural validation passes, when an ARA needs an objective epistemic critique before publication or release.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchchroma
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchcreative-thinking-for-research
Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchcrewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchdeepspeed
Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchevolving-ai-agents
Provides 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.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchexperiment-tracking-swanlab
Provides guidance for experiment tracking with SwanLab. Use when you need open-source run tracking, local or self-hosted dashboards, and lightweight media logging for ML workflows.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchgptq
Post-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.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchgrpo-rl-training
Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchguidance
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchhqq-quantization
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchhuggingface-tokenizers
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchimplementing-llms-litgpt
Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchlangsmith-observability
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchllama-factory
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchllamaguard
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日
orchestra-researchllava
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
- 導入数
- 2
- GitHub Stars
- 1.3万
- 更新日
- 6月16日