Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
46,700 skills from 2,243 repositories · updated 17 hours ago
46,700 skills
- golden-pdf-chyusufkaraaslan/Skill_SeekersUse when testing chapter categorizationDocumentsNo warnings★ 15.2K↓ —
- ray-trainOrchestra-Research/AI-Research-SKILLsDistributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.OtherNo warnings★ 14K↓ —
- prompt-guardOrchestra-Research/AI-Research-SKILLsMeta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast (<2ms GPU). Multilingual (8 languages). Deploy with HuggingFace or batch processing for RAG security.SecurityNo warnings★ 14K↓ —
- fine-tuning-with-trlOrchestra-Research/AI-Research-SKILLsFine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.OtherNo warnings★ 14K↓ —
- distributed-llm-pretraining-torchtitanOrchestra-Research/AI-Research-SKILLsProvides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.OtherNo warnings★ 14K↓ —
- nemo-curatorOrchestra-Research/AI-Research-SKILLsGPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.MediaNo warnings★ 14K↓ —
- pineconeOrchestra-Research/AI-Research-SKILLsManaged vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.DevOpsNo warnings★ 14K↓ —Also in 1 other repo
- autogpt-agentsOrchestra-Research/AI-Research-SKILLsAutonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.DevOpsNo warnings★ 14K↓ —
- experiment-tracking-swanlabOrchestra-Research/AI-Research-SKILLsProvides 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.OtherNo warnings★ 14K↓ —
- mlflowOrchestra-Research/AI-Research-SKILLsTrack ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platformDevOpsNo warnings★ 14K↓ —
- qdrant-vector-searchOrchestra-Research/AI-Research-SKILLsHigh-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.OtherNo warnings★ 14K↓ —
- altoranksickn33/agentic-awesome-skillsRun AltoRank through its hosted MCP server: readiness audits, Search Console, keyword research, and SEO drafts into a review queue.ScienceNo warnings★ 48.6K↓ —
- faissOrchestra-Research/AI-Research-SKILLsFacebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.OtherNo warnings★ 14K↓ —
- opencreator-runtimekrillinai/OpenCreatorOpenCreator 内部 Creator Agent 的稳定运行规则，仅由应用自动安装和激活。OtherNo warnings★ 13.9K↓ —
- krillinai-coverkrillinai/OpenCreatorUse when generating a cover image with the KrillinAI CLI from a complete image prompt, including validating image-provider configuration and inspecting the generated image and saved prompt.MediaNo warnings★ 13.9K↓ —
- krillinai-render-verticalkrillinai/OpenCreatorUse when rendering portrait videos with KrillinAI CLI, including converting source video to vertical format, adding short bilingual subtitles, rendering dubbed vertical videos, and checking vertical subtitle readability.MediaNo warnings★ 13.9K↓ —
- krillinai-subtitlekrillinai/OpenCreatorUse when generating subtitles with KrillinAI CLI from a YouTube link, Bilibili/local video, or existing media, including platform caption download, Whisper fallback, translation, bilingual SRT, and short vertical subtitle output.MediaNo warnings★ 13.9K↓ —
- krillinai-pipelinekrillinai/OpenCreatorUse when validating or documenting a multi-stage KrillinAI CLI output plan; the current pipeline command supports dry-run planning only, not end-to-end execution.PlanningNo warnings★ 13.9K↓ —
- krillinai-ttskrillinai/OpenCreatorUse when generating target-language dubbing with KrillinAI CLI from SRT subtitles, including TTS audio creation and optional dubbed video generation.MediaNo warnings★ 13.9K↓ —
- skill-builderyusufkaraaslan/Skill_SeekersAutomatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.OtherNo warnings★ 15.2K↓ —
- golden-jupyter-topicsyusufkaraaslan/Skill_SeekersUse when testing the golden_jupyter_topics golden buildTestingNo warnings★ 15.2K↓ —
- golden-jupyter-diryusufkaraaslan/Skill_SeekersUse when testing the golden_jupyter_dir golden buildTestingNo warnings★ 15.2K↓ —
- golden-chat-topicsyusufkaraaslan/Skill_SeekersUse when testing the golden_chat_topics golden buildTestingNo warnings★ 15.2K↓ —
- golden-chat-singleyusufkaraaslan/Skill_SeekersUse when testing the golden_chat_single golden buildTestingNo warnings★ 15.2K↓ —
llama-cpp
Orchestra-Research/AI-Research-SKILLs
DevOpsUpdated Oct 11, 2026
From the author
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
Install
npx skills add Orchestra-Research/AI-Research-SKILLs --skill llama-cpp -a claude-code
Installs to .claude/skills/llama-cpp/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyUses the networkLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 93
Security100
Provenance90
Maintenance100
Licence100
Adoption65
Files (4)
- SKILL.md
- references/optimization.md
- references/quantization.md
- references/server.md