Skills · category
Research skills and plugins
Public Claude skills and plugins for research, each with Waxell's security verdict and the findings behind it.
- 4,093 reviewed
- 3,091 no issues
- 932 to review
- 52 high risk
849 resultsResearch
fine-tuning-with-trlorchestra-researchFine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward… Review findingsResearchAI & agents14k- verl-rl-trainingorchestra-researchProvides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or… Review findingsResearchAI & agents14k
- constitutional-aiorchestra-researchAnthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with… No issuesResearchAI & agents14k
- llamaguardorchestra-researchMeta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons,… Review findingsResearchAI & agents14k
- nemo-guardrailsorchestra-researchNVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking,… Review findingsResearchAI & agents14k
- prompt-guardorchestra-researchMeta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast… Review findingsResearchData & analytics14k
- huggingface-accelerateorchestra-researchSimplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP.… Review findingsResearchEngineering14k
- deepspeedorchestra-researchExpert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam,… Review findingsResearchSales & marketing14k
- training-llms-megatronorchestra-researchTrains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training… Review findingsResearchSales & marketing14k
- pytorch-fsdp2orchestra-researchAdds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed… No issuesResearchDocuments14k
- pytorch-lightningorchestra-researchHigh-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal… Review findingsResearchEngineering14k
- ray-trainorchestra-researchDistributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in… Review findingsResearchAI & agents14k
- lambda-labs-gpu-cloudorchestra-researchReserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH… High riskResearchAI & agents14k
- modal-serverless-gpuorchestra-researchServerless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management,… Review findingsResearchEngineering14k
- skypilot-multi-cloud-orchestrationorchestra-researchMulti-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across… Review findingsResearchAI & agents14k
- awq-quantizationorchestra-researchActivation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models… Review findingsResearchAI & agents14k
- quantizing-models-bitsandbytesorchestra-researchQuantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit… Review findingsResearchAI & agents14k
- optimizing-attention-flashorchestra-researchOptimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers… Review findingsResearchDocuments14k
- gguf-quantizationorchestra-researchGGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or… Review findingsResearchEngineering14k
- gptqorchestra-researchPost-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when… Review findingsResearchDocuments14k
- hqq-quantizationorchestra-researchHalf-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing… Review findingsResearchData & analytics14k
- ml-training-recipesorchestra-researchBattle-tested PyTorch training recipes for all domains, LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics,… No issuesResearchEngineering14k
- evaluating-code-modelsorchestra-researchEvaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code… Review findingsResearchEngineering14k
- evaluating-llms-harnessorchestra-researchEvaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality,… Review findingsResearchDocuments14k
- nemo-evaluator-sdkorchestra-researchEvaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when… Review findingsResearchEngineering14k
- llama-cpporchestra-researchRuns LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel… No issuesResearchAI & agents14k
- sglangorchestra-researchFast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding,… Review findingsResearchProductivity14k
- tensorrt-llmorchestra-researchOptimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs… No issuesResearchEngineering14k
- serving-llms-vllmorchestra-researchServes LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing… Review findingsResearchEngineering14k
- mlfloworchestra-researchTrack ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow -… Review findingsResearchEngineering14k
- experiment-tracking-swanlaborchestra-researchProvides guidance for experiment tracking with SwanLab. Use when you need open-source run tracking, local or self-hosted dashboards, and… Review findingsResearchData & analytics14k
- tensorboardorchestra-researchVisualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with… Review findingsResearchData & analytics14k
- weights-and-biasesorchestra-researchTrack ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model… Review findingsResearchData & analytics14k
- evolving-ai-agentsorchestra-researchProvides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when… Review findingsResearchAI & agents14k
- autogpt-agentsorchestra-researchAutonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent… No issuesResearchEngineering14k
- crewai-multi-agentorchestra-researchMulti-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on… Review findingsResearchProductivity14k
- langchainorchestra-researchFramework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google),… Review findingsResearchEngineering14k
- llamaindexorchestra-researchData framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying.… Review findingsResearchData & analytics14k
- chromaorchestra-researchOpen-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by… Review findingsResearchData & analytics14k
- faissorchestra-researchFacebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and… Review findingsResearchAI & agents14k
- pineconeorchestra-researchManaged vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata… Review findingsResearchData & analytics14k
- qdrant-vector-searchorchestra-researchHigh-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast… Review findingsResearchAI & agents14k
- sentence-transformersorchestra-researchFramework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity,… Review findingsResearchDesign14k
- dspyorchestra-researchBuild complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy -… Review findingsResearchEngineering14k
- guidanceorchestra-researchControl LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step… Review findingsResearchEngineering14k
- instructororchestra-researchExtract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type… Review findingsResearchData & analytics14k
- outlinesorchestra-researchGuarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers,… Review findingsResearchEngineering14k
- langsmith-observabilityorchestra-researchLLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against… Review findingsResearchEngineering14k
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Inside your organization, Waxell scans each skill and plugin before anyone installs it, approves what passes and publishes it to a private marketplace, and puts every MCP tool call behind one governed URL.
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SOC 2 Type II attested · ISO/IEC 27001:2022 certified · HIPAA with a BAA · aligned to the EU AI Act and NIST AI RMF