Total 50,658 skills, AI & Machine Learning has 8491 skills
Showing 12 of 8491 skills
LLM prompt testing, evaluation, and CI/CD quality gates using Promptfoo. Invoke when: - Setting up prompt evaluation or regression testing - Integrating LLM testing into CI/CD pipelines - Configuring security testing (red teaming, jailbreaks) - Comparing prompt or model performance - Building evaluation suites for RAG, factuality, or safety Keywords: promptfoo, llm evaluation, prompt testing, red team, CI/CD, regression testing
Anti-footgun protocol for AI-assisted coding. Always active during coding tasks to enforce simplicity-first thinking, surface assumptions, and prevent scope creep. Explicit checkpoints available via "cg pre", "cg post", "cg simplify". Triggers on: any coding task, code review requests, refactoring, or when user says "cg" or "check".
Invokes Gemini CLI as a second opinion. Use for reviewing plans, code, architectural decisions, AND for analyzing large volumes of content that benefit from Gemini's 1M+ token context window.
Guidelines for creating AI agent skills. Use when writing new skills, documenting coding patterns, or reviewing skill files. Triggers when creating or modifying files in the skills/ directory.
Set up and manage local skills for automatic matching and invocation
Consult Gemini AI for architecture alternatives, design trade-offs, and brainstorming. Use when seeking different perspectives on design, evaluating architectural approaches, comparing solutions, or generating creative ideas.
Write and optimize prompts for AI-generated outcomes across text and image models. Use when crafting prompts for LLMs (Claude, GPT, Gemini), image generators (Midjourney, DALL-E, Stable Diffusion, Imagen, Flux), or video generators (Veo, Runway). Covers prompt structure, style keywords, negative prompts, chain-of-thought, few-shot examples, iterative refinement, and domain-specific patterns for marketing, code, and creative writing.
Guide for creating effective skills. Use when you want to create a new skill (or update an existing skill) that extends an agent with specialized workflows, tool integrations, or repo conventions.
MLflow experiment tracking via Python API. TRIGGERS - MLflow metrics, log backtest, experiment tracking, search runs.
LangGraph checkpointing and persistence. Use when implementing fault-tolerant workflows, resuming interrupted executions, debugging with state history, or avoiding re-running expensive operations.
Generate skills from documentation websites. Use when asked to create skills from docs, convert documentation to agent skills, or crawl a docs site.
Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM workflows.