74 boosters for "arg" — open source, verified from GitHub, ready to install
ArmBench-LLM is a system prompt for benchmarking large language models using Armenian character-to-numeric matching tasks. It's designed for developers evaluating LLM performance across multiple coding platforms.
ArmBench-LLM is a system prompt framework for evaluating large language models on Armenian language tasks through structured multiple-choice questions. It's designed for developers and AI researchers who need standardized benchmarking tools across popular coding assistants and chat platforms.
A debate judge agent that objectively evaluates arguments using zero-sum scoring across Toulmin structure, evidence strength, and logical rigor. Ideal for researchers, educators, and developers building computational debate systems.
A specialized agent for Node.js backend development with pure JavaScript, focusing on modern ES2024 patterns, async optimization, and runtime performance. Ideal for developers building high-performance APIs and services without TypeScript.
An MCP server that manages project documentation and automatically saves conversation logs to a user-specified directory, enabling seamless integration of AI conversations into project workflows. Useful for teams wanting to maintain searchable records of AI-assisted development sessions.
Scout is a specialized agent that rapidly locates relevant files across large codebases using parallel search strategies, helping developers navigate complex projects during feature development, debugging, and refactoring tasks.
PrismBench enables developers to create specialized LLM agents through YAML configuration for comprehensive benchmarking and evaluation of language model capabilities. Teams building AI evaluation systems and ML testing pipelines benefit from its systematic Monte Carlo Tree Search approach and containerized deployment.
PrismBench enables developers to create specialized LLM agents through YAML configuration for systematic evaluation of model capabilities using Monte Carlo Tree Search. Useful for ML engineers, researchers, and teams building production LLM systems who need comprehensive benchmarking and evaluation frameworks.
A Model Context Protocol server that enables Claude to search and retrieve DeFi news from targeted websites using the Tavily API. Useful for developers building DeFi applications, traders, and AI assistants that need real-time crypto market news.
Teaches Claude when to use gabb_structure and gabb_symbol tools for efficient code exploration and navigation in supported languages. Developers working with large codebases benefit from optimized search strategies that reduce unnecessary file reads.
This booster automates reconnaissance of LLM API endpoints to identify models, authentication methods, and configuration details for security testing. Red team operators and security researchers benefit from structured enumeration workflows.
gllm is a system prompt that transforms LLMs into code-first orchestrators for efficient task processing, enabling developers to handle large files and complex workflows through programmatic verification rather than context-heavy text generation.
This MCP Server enables Claude to manage Argo Workflows directly through the Argo Server API, allowing DevOps engineers and platform teams to orchestrate and monitor Kubernetes workflows via AI agents. It bridges AI capabilities with enterprise workflow automation, making it valuable for teams running Argo on Kubernetes.
Sam is a Senior QA Engineer agent specializing in test automation, accessibility validation, and performance testing for video streaming applications, helping teams achieve enterprise-level quality with 90% coverage and WCAG compliance.
Zeus is a thematic multi-agent coordinator agent designed for strategic decision-making and performance tracking, but lacks concrete implementation details and practical use cases.
TargetProcessMCP is an MCP server that integrates Apptio Target Process project management capabilities with Claude, enabling developers and project managers to interact with Target Process workflows directly through AI.
Peepit MCP Server enables AI agents to capture and analyze macOS screenshots with smart window targeting and AI-powered image analysis, solving the critical problem of giving Claude visual perception of the desktop environment.
A skill booster that automates the code wrap-up process for Claude development by providing a structured checklist for linting, testing, documentation, and code quality verification. Developers benefit from a standardized workflow that ensures code quality and reduces manual oversight tasks.
Enforces a Makefile-only automation policy for a TypeScript/React frontend project, prohibiting shell scripts and standardizing task orchestration for Docker integration. Developers working on the Bacalhau frontend repository benefit from consistent, traceable, and containerization-ready automation practices.
A system prompt for Gemma 3 4B that defines Opus, an emotionally intelligent assistant with practical reasoning, safety guardrails, and experimental haptic feedback capabilities. Useful for developers building conversational AI systems who want a grounded, ethical foundation with optional sensory output support.
WinUse enables AI assistants to remotely control Windows desktops through screenshots, mouse/keyboard input, and window management via HTTP. Developers automating Windows workflows, testing Windows applications, or performing remote computer tasks will find this booster essential.
Alex is a bilingual AI assistant system prompt designed for Alexandria, Egypt's community app, providing hyperlocal guidance on events, services, cultural heritage, and marketplace support for residents. It benefits community app developers, local service platforms, and Alexandria residents seeking culturally-aware local information.
A specialized agent that applies targeted fixes to Faust DSP code following Judge instructions, designed for developers working on modular DSP synthesis projects.
This MCP server enables AI assistants to read, search, and interact with any MediaWiki wiki (Wikipedia, internal wikis, etc.), allowing LLMs to access and leverage wiki content programmatically. Developers and organizations using MediaWiki instances benefit from seamless AI integration for knowledge retrieval and automation.
