134 boosters for "lm" — open source, verified from GitHub, ready to install
A system prompt that enables LLM-based news headline tagging by categorizing stories into People, Topic, and Geography tags with structured JSON output. Useful for developers building news processing pipelines or content classification systems.
Intent Kit provides Cursor rules for building hierarchical intent-driven Python workflows with LLMs, enabling developers to create structured, context-aware automation systems. It's useful for developers building complex AI-driven applications that require intent classification and conditional execution.
A JavaScript-based system for dynamically creating and modifying AI agents without recompilation, enabling local LLM developers to test and share agent configurations interactively.
A practical guide to writing maintainable, debuggable LLM agent code by addressing unique failure modes like non-determinism, opaque tool calls, and prompt-logic coupling. Developers building Claude-based agents will benefit from these patterns.
Aura is a system prompt that instructs Claude to write code as an expert Lx compiler interface, enforcing LLM-friendly language rules like exhaustiveness, no loops, and explicit effects. It benefits developers learning or writing Lx code who need consistent, compiler-compatible output from Claude.
An expert AI engineer agent that helps developers build production-ready LLM applications, RAG systems, and intelligent agents with deep knowledge of modern AI stacks. Ideal for teams building chatbots, AI-powered features, and enterprise AI integrations.
EROS is an AI specialist agent for designing behavior-based matching algorithms, LLM integration, and recommendation systems in dating applications. It helps backend, frontend, and database engineers implement ethical, explainable AI matching features.
An MCP server that integrates llmstxt documentation fetching into Claude Desktop and Claude Code, enabling developers to access and reference documentation within their AI-assisted workflows.
Mcp Tool Factory generates MCP servers from natural language, OpenAPI specs, databases, GraphQL, and ontologies, supporting 10+ LLM providers. Developers building AI agents and tool ecosystems benefit from automated server generation without manual boilerplate.
Heuristic scoring (no AI key configured).
This skill automates downloading books from Anna's Archive and uploading them to Google NotebookLM for AI-powered document analysis. It's useful for researchers and students who want to create knowledge bases from books without manual uploads.
A multi-LLM system prompt for coordinating development across Claude, ChatGPT, Cursor, and Windsurf with architecture guidelines and agent synchronization protocols. Primarily benefits teams using multiple AI assistants in coordinated workflows.
MetehanGZL Pokemcp provides developers with detailed Pokémon data and information through a standardized MCP interface, enabling AI assistants to access comprehensive game information for building Pokémon-related applications and features.
This MCP server integrates with Civic Plus See Click Fix, enabling users to access and interact with civic data through an LLM interface. It's useful for municipal staff, developers, and citizens working with See Click Fix complaint and issue tracking systems.
This MCP server integrates an LLM Search Engine into Claude and Cursor, enabling developers to perform web searches directly within their AI workflows. It's useful for developers who need real-time information retrieval capabilities in their AI-assisted coding and analysis tasks.
An LLM-optimized TickTick task management MCP server that reduces token costs by 70% through intelligent time handling, enabling efficient AI-assisted task automation for productivity-focused developers and AI assistants.
A specialized agent that systematically crafts, tests, and optimizes prompts for LLMs through multiple cognitive modes (generative, critical, evaluative, informative) and performance measurement. Ideal for AI engineers, prompt researchers, and developers seeking to maximize LLM output quality.
"id": "ai.byteray/byteray-mcp", "name": "ByteRay AI", "description": "AI-augmented binary vulnerability analysis with 38 MCP tools for taint tracing and zero-day hunting"
A specialized agent that systematically crafts and optimizes prompts for LLMs and AI systems through iterative refinement and performance measurement. Ideal for AI engineers, prompt designers, and developers who need to maximize LLM effectiveness across applications.
A system prompt that enables LLMs to trigger local development tasks (git, shell commands) via webhooks. Intended for developers using Claude, Cursor, or similar AI coding tools who want voice-triggered automation.
Cursor rules for Learnology AI LMS that guide developers to wrap UI components with LunaContextElement and provide structured context data for AI assistant integration. Useful for teams building AI-enhanced learning management systems.
An expert prompt engineering agent that optimizes prompts for LLMs and AI systems, helping developers build better AI features and improve agent performance through proven prompt patterns and techniques.
Converts deepagents' single `task` tool into individual `AgentTool` instances for cleaner sub-agent delegation in adk-deepagents. Developers building hierarchical multi-agent systems benefit from this more modular approach to agent composition.
