Loading...
Loading...
Found 4,646 Skills
Use when the user is doing AI/ML work in a scientific domain — biology, chemistry, physics, astronomy, climate, genomics, materials science, medicine, ecology, energy, conservation, engineering, mathematics, scientific reasoning, drug discovery, protein design, weather modeling, theorem proving, single-cell, PDE solving, or anything similar. Hugging Science (huggingscience.co) is a curated catalog of scientific datasets, models, blog posts, and interactive Spaces; the `hugging-science` org on Hugging Face hosts community datasets, models, and demo Spaces. This skill helps you discover the right resource AND actually use it — loading datasets via `datasets`, running models via `transformers` or the HF Inference API, calling Spaces like BoltzGen via `gradio_client`, and citing blog posts for methodology. Trigger this skill whenever a user mentions a scientific ML task, asks for "a dataset/model for X" where X is a scientific topic, wants to fine-tune on scientific data, asks about protein / molecule / genome / climate / materials / astronomy / pathology / weather ML, or needs AI tools for research — even if they never say "Hugging Science" explicitly. The catalog is purpose-built for LLM agents (it ships an `llms-full.txt`); prefer it over generic web search for these tasks.
Use whenever researching a technical question — a library, tool, API, error, version, or "what's the best way to X" — or whenever you're about to answer from memory. Forces multiple real searches over primary sources (official docs, source code, high-vote Stack Overflow, maintainer blogs) instead of one search plus training-data filler, and rejects SEO content-farm slop. Trigger on "research X", "look into", "what's the best library for", "how does X work", "is this still true", "find out".
Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.
Build backend AI with Vercel AI SDK v6 stable. Covers Output API (replaces generateObject/streamObject), speech synthesis, transcription, embeddings, MCP tools with security guidance. Includes v4→v5 migration and 15 error solutions with workarounds. Use when: implementing AI SDK v5/v6, migrating versions, troubleshooting AI_APICallError, Workers startup issues, Output API errors, Gemini caching issues, Anthropic tool errors, MCP tools, or stream resumption failures.
Medusa headless commerce - modules, workflows, API routes, admin UI
Production gRPC in Go: protobuf layout, codegen, interceptors, deadlines, error codes, streaming, health checks, TLS, and testing with bufconn
Guide for authoring Pulumi ComponentResource classes. Use when creating reusable infrastructure components, designing component interfaces, setting up multi-language support, or distributing component packages.
Comprehensive guide for building AI agents that interact with Solana blockchain using SendAI's Solana Agent Kit. Covers 60+ actions, LangChain/Vercel AI integration, MCP server setup, and autonomous agent patterns.
Provides architecture guidance for multi-tenant platforms on Cloudflare or Vercel. Use when defining domain strategy, tenant identification, isolation, routing, custom domains, and plan/limit mapping.
Designs CloudFormation stack structure, nested stacks, and resource organization. Use when designing CloudFormation infrastructure, organizing resources into stacks, or planning nested stack hierarchies.
Analyze and optimize AWS costs with recommendations for Reserved Instances, right-sizing, and resource cleanup. Use when reducing AWS spending, analyzing costs, or optimizing cloud infrastructure expenses.
This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment. Use this for generating GitHub Actions workflows, GitLab CI configs, CircleCI configs, or other CI/CD platform configurations. Ideal for setting up automated pipelines for Node.js/Next.js applications, including linting, testing, building, and deploying to platforms like Vercel, Netlify, or AWS.