Skill UI

A comprehensive guide to setting up a fast, reproducible local development workflow for Groq applications. This setup includes structured project scaffolding, implementing singleton clients, defining model constants, and providing isolated unit tests with mocking, alongside live integration tests. Ideal for developers building low-latency LLM applications and ensuring rapid iteration cycles.

A comprehensive guide to configuring a structured, local development environment for LangChain applications. It covers setting up project architecture, managing dev dependencies, and implementing a two-tiered testing strategy: isolated unit tests using mocked LLMs (for fast, API-free testing) and robust integration tests using real API providers. Ideal for establishing a reliable, rapid iteration workflow.

This guide provides a comprehensive local development setup for LLM applications using Langfuse. It enables fast iteration cycles, real-time trace debugging, and hot reloading, making it ideal for developers building and testing complex AI workflows locally. Instructions cover environment setup, advanced SDK usage, and optional self-hosted Docker deployment.

This skill automates the setup and configuration of Ollama, allowing users to deploy Large Language Models (LLMs) locally. It performs system assessment (OS, GPU, RAM), selects optimal models based on hardware availability, and handles installation across macOS, Linux, and Docker. Use this when you require free, self-hosted AI alternatives, need offline inference capabilities, or wish to eliminate reliance on costly hosted API services.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Convert PDF, Office, HTML, CSV, EPUB and other documents into structure-preserving Markdown with Microsoft MarkItDown. Covers safe local and stream conversion, batch workflows, plugins, vision OCR, Azure extraction, and MCP integration for search and LLM/RAG ingestion.

Analyzes Screenpipe history windows to detect repeated research workflows, match existing skills, and stage new skill drafts for review. Requires local Screenpipe daemon on localhost:3030 with optional LLM backend. Privacy-focused with data redaction before LLM processing. Use only when user explicitly requests workflow analysis.

This skill automates the Test-Driven Development (TDD) repair loop. Given a failing unit test, it spawns a bounded, headless LLM agent to automatically modify the source code until the test passes. It closes the development loop by treating the test's pass/fail status as the definitive fitness function, ideal for CI failure triage and local TDD workflows.

A comprehensive guide for building AI agents in Dart with Genkit, covering flows, tools, plugins, schemas, and the Genkit CLI for local development. Ideal for integrating LLMs into Dart or Flutter applications.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Configure a Mac mini as a reliable local LLM server with remote access, observability, and power-safe operation. Use when building an always-on private AI inference server on Apple Silicon.

Deploy a local LLM stack with Ollama, Open WebUI, and LiteLLM for offline, privacy-first AI workloads. Covers installation, model selection, Docker Compose setup, API usage, and custom Modelfiles for development environments.