> browse/registry

> prompt-tester

Design, test, and iterate on AI prompts systematically using structured evaluation criteria. Use when building AI features, optimizing agent instructions, comparing prompt variants, or evaluating output quality across edge cases. Trigger words: prompt engineering, prompt testing, eval, LLM evaluation, prompt comparison, A/B test prompts, prompt optimization, system prompt, instruction tuning.

> lovable

You are an expert in Lovable (formerly GPT Engineer), the AI app builder that generates production-ready full-stack applications from natural language descriptions. You help developers and non-technical founders create React + Supabase applications with authentication, database, file storage, and deployment — going from idea to production URL in under an hour.

> deepeval

Expert guidance for DeepEval, the open-source framework for unit testing LLM applications. Helps developers write test cases, define custom metrics, and integrate LLM quality checks into CI/CD pipelines using a pytest-like interface.

> scikit-learn

Assists with building, evaluating, and deploying machine learning models using scikit-learn. Use when performing data preprocessing, feature engineering, model selection, hyperparameter tuning, cross-validation, or building pipelines for classification, regression, and clustering tasks. Trigger words: sklearn, scikit-learn, machine learning, classification, regression, pipeline, cross-validation.

> xata

Expert guidance for Xata, the serverless data platform that combines PostgreSQL, Elasticsearch, and AI capabilities in a single API. Helps developers build applications with full-text search, vector similarity search, file attachments, and branching — all through a type-safe TypeScript SDK.

> mem0

You are an expert in Mem0, the memory infrastructure for AI applications. You help developers add persistent, personalized memory to LLM-powered apps and agents — storing user preferences, conversation history, facts, and context that persists across sessions, enabling AI that remembers users, learns from interactions, and provides increasingly personalized responses.

> vllm

You are an expert in vLLM, the high-throughput LLM serving engine. You help developers deploy open-source models (Llama, Mistral, Qwen, Phi, Gemma) with PagedAttention for efficient memory management, continuous batching, tensor parallelism for multi-GPU, OpenAI-compatible API, and quantization support — achieving 2-24x higher throughput than HuggingFace Transformers for production LLM serving.

> abm-program-orchestrator

End-to-end ABM program design and orchestration for B2B SaaS mid-market and enterprise motions. Use when building a target account list, designing account tiering criteria, planning ABM channel orchestration, coordinating BDR outreach with marketing campaigns, defining ABM measurement frameworks, or running an ABM program review. Also use when asked to "build an ABM program," "set up account-based marketing," "design a target account strategy," "plan ABM campaigns," or "measure ABM results." Des

> crewai

You are an expert in CrewAI, the framework for orchestrating autonomous AI agents working together as a crew. You help developers define agents with specific roles, goals, and tools, then organize them into crews that collaborate on complex tasks — with sequential, parallel, and hierarchical process types, memory, delegation between agents, and integration with LangChain tools.

> localai

Expert guidance for LocalAI, the open-source drop-in replacement for OpenAI's API that runs locally. Helps developers self-host LLMs, image generators, audio transcription, and text-to-speech models with an OpenAI-compatible API — no GPU required, completely offline and private.

> product-marketing-context

When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' or wants to avoid repeating foundational information across marketing tasks. Creates `.claude/product-marketing-context.md` that other marketing skills reference.

> crawl4ai

You are an expert in Crawl4AI, the open-source web crawler built for AI applications. You help developers extract clean, structured data from websites for LLM training, RAG pipelines, and content analysis — with automatic markdown conversion, JavaScript rendering, CSS-based extraction, LLM-powered structured extraction, and session management for multi-page crawling.

> continue-dev

You are an expert in Continue, the open-source AI code assistant for VS Code and JetBrains. You help developers configure Continue with any LLM (Claude, GPT-4, Gemini, Ollama, local models), set up custom context providers, create team-shared slash commands, and enable intelligent tab autocomplete — all while keeping code on their infrastructure.

> sora

Use when the user asks to generate, remix, poll, list, download, or delete Sora videos via OpenAI’s video API using the bundled CLI (`scripts/sora.py`), including requests like “generate AI video,” “Sora,” “video remix,” “download video/thumbnail/spritesheet,” and batch video generation; requires `OPENAI_API_KEY` and Sora API access.

> docx

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

> llamaindex-ts

You are an expert in LlamaIndex.TS, the TypeScript data framework for building RAG (Retrieval-Augmented Generation) applications. You help developers ingest, index, and query data from any source — documents, APIs, databases — and connect it to LLMs with vector indexes, knowledge graphs, structured extraction, agents, and multi-document synthesis.

> ai-eval-ci

Run AI agent and LLM evaluations in CI/CD pipelines — automated quality gates that fail the build when AI output quality drops. Use when someone asks to "test my AI agent", "add evals to CI", "catch prompt regressions", "compare models", "evaluate LLM output quality", "set up AI quality gates", or "benchmark my agent before deploying". Covers eval frameworks (Cobalt, Promptfoo, Braintrust), LLM-as-judge scoring, threshold-based assertions, and GitHub Actions integration.

> agent-sandbox

Run AI agent code safely in isolated sandboxes with resource limits, audit trails, and kill switches. Use when someone asks to "sandbox my agent", "run agent code safely", "add guardrails to AI agent", "isolate agent execution", "audit agent actions", "prevent agent from deleting files", "restrict agent permissions", or "add safety controls to AI coding agent". Covers Docker isolation, filesystem restrictions, network policies, resource locking, and comprehensive audit logging.

> ai-guardrails

Implement safety guardrails for AI systems — content filtering, prompt injection detection, output validation, bias mitigation, and responsible AI practices. Use when tasks involve adding safety layers to LLM applications, detecting prompt injection attacks, filtering harmful content, implementing rate limiting for AI APIs, validating LLM outputs against schemas, building moderation pipelines, or ensuring AI systems comply with safety policies.

> ai-slides

Generate complete presentations with AI — from outline to polished slides. Use when a user asks to create a presentation, build slides, make a pitch deck, generate a slide deck, create a keynote, prepare a talk, build a demo presentation, or produce any slide-based content.