LLM & AI Agent Skills

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.

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

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

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

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

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

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

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.

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

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

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.

Search and retrieve biomedical data — genes, variants, clinical trials, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. 15 sources including PubMed, ClinicalTrials.gov, ClinVar, OncoKB, Reactome, UniProt, PharmGKB, OpenFDA, Monarch. Use when asked about gene function, variant pathogenicity, trial matching, drug safety, resistance mechanisms, hereditary syndromes, or literature evidence.

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

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

You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur

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.

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

The open-source alternative to Google's Code Wiki — with MCP. Index any codebase with tree-sitter, generate docs with your LLM, serve them through a full-featured docs site, and expose everything as tools for coding agents via MCP. Like Notion for code agents. Index a project and generate documentation. Defaults to the current directory. Start the docs server. Manage API keys and provider settings

Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces).

Guide for upgrading Stripe API versions and SDKs

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

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.