LLM & AI Agent Skills

Screenpipe brand style guide. Reference this when designing UI components, writing copy, or making visual decisions.

Persistent memory for Claude Code. Also: loop detection, scope guards, code analysis, and a local LLM for second opinions. Claude Code forgets everything between sessions and after context compaction. Mini Claude provides: - Checkpoints - Save task state, auto-restore after compaction - Mistake memory - Log errors, get warned next time you touch that file - Decision memory - Log WHY you chose some

Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

Edit code → commit → run benchmark → measure metric → keep improvement or revert → repeat forever. Works for any optimization target: LLM training loss, test speed, bundle size, build time, Lighthouse scores, and more. Inspired by Karpathy's autoresearch, pi-autoresearch, and litesearch. This plugin provides two skills that work together. Autoresearch is the core engine (works for any metric), and

Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.

MCP Manager for Claude Desktop A simple web GUI to manage Model Context Protocol (MCP) servers for the Claude Desktop app on MacOS easily. Just follow the instructions and paste a few commands to give your Claude app instant superpowers. The Model Context Protocol (MCP) enables Claude to access private data, APIs, and other services to answer questions and perform actions on your behalf. Learn mor

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

AI-powered developer workflows with cost optimization and pattern learning. Run code review, debugging, testing, and release workflows from your terminal or Claude Code. Smart tier routing saves 34-86% on LLM costs. -brightgreen) Empathy Framework is evolving to focus exclusively on Anthropic/Claude to unlock features impossible with multi-provider abstraction: - 📦 Prompt Caching: 90% cost reduct

You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.

Use when auditing a codebase for semantic duplication - functions that do the same thing but have different names or implementations. Especially useful for LLM-generated codebases where new functions are often created rather than reusing existing ones.

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.

This project uses the Model Context Protocol (MCP) to let LLMs directly understand and generate Max patches. Video link. Acknowledgement: the patch being explained is downloaded from here. Text comments in the original file are deleted. Check out the full video where you can listen to the synthesised sounds. The LLM agent has access to the official documentation of each object, as well as objects

Give your agents memory that survives the session, so they stop re-deriving what they already learned and stop repeating past mistakes. Hybrid recall (BM25 + dense + RRF), bi-temporal history, and AES-256-GCM at rest, exposed as 55+ MCP tools that work with any host. 73.8% on LongMemEval's official harness (vs Zep 63.8%, Mem0 49.0%). One binary. One file. No Docker. No Postgres. No cloud. Local-fi

Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.

A tool similar to cloc, sloccount and tokei. For counting the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages. Goal is to be the fastest code counter possible, but also perform COCOMO calculation like sloccount, LOCOMO estimation for LLM-based development costs, estimate code complexity similar to cyclomatic complexity calculators and prod

Advanced search and retrieval for web crawler data. With mcp-server-webcrawl, your AI client filters and analyzes web content under your direction or autonomously. The server includes a fulltext search interface with boolean support, and resource filtering by type, HTTP status, and more. mcp-server-webcrawl provides the LLM a complete menu with which to search, and works with a variety of web craw

A Model Context Protocol server for Zotero integration. It gives any LLM full access to your Zotero library: search, organize, add papers by DOI, import PDFs, read full-text content, and inject live citations into Word documents. The server is designed to be usable by any LLM without external documentation. On connection, it sends workflow instructions via the MCP instructions field, and each tool

The goal of this MCP is to: - Consolidate ESP-IDF and related project commands in one place. - Simplify getting started using only LLM communication. Simply find a command that is missing from this MCP and create a PR for it! If you want someone to help you with this implementation, just open an issue. This project is currently a Proof of Concept (PoC) for an MCP server tailored for ESP-IDF workfl

aka Vibe Debugging This is an MCP Server and VS Code extension which enables claude to interactively debug and evaluate expressions. That means it should also work with other models / clients etc. but I only demonstrate it with Claude Desktop and Continue here. It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode. 1. Download the extension from re

See a demo here: https://www.youtube.com/watch?v=KG6TMLD8GmA Upload, edit, search, and generate videos from everyone's favorite LLM and Video Jungle. You'll need to sign up for an account at Video Jungle in order to use this tool, and add your API key. The server implements an interface to upload, generate, and edit videos with: - Custom vj:// URI scheme for accessing individual videos and project

An MCP (Model Context Protocol) server that brings authoritative medical information into AI coding environments like Cursor and Claude Desktop. - 🔒 Your Data Never Leaves – Runs 100% locally; no tracking, no logs, no cloud - 🆓 No API Keys – Works out of the box, zero configuration - 🏥 Authoritative Sources – FDA, WHO, PubMed, RxNorm, Google Scholar, AAP, pediatric journals - ⚡ Easy Setup – One

An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data. - osm-mcp-server: The main server, available for public use. This server provides LLMs with tools to interact with OpenStreetMap data, enabling location-based applications to: - Geocode addresses and place names to coordinates - Reverse geocode coordinates to addresses - Find

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

Zero-hallucination answers • Gemini Deep Research • 14 Security Layers • Enterprise Compliance What's New 2026 • Deep Research • Document API • Create Notebooks • Security • Install - 🔍 Query your NotebookLM notebooks — source-grounded, zero-hallucination answers - 📚 Create & manage notebooks programmatically — no manual clicking - 🎙️ Generate audio overviews — podcast-style summaries of your d