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Version-controlled system prompts and integration settings specifically for Claude Code agent environments.
Explore 14 awesome GitHub repositories matching artificial intelligence & ml · Claude Code Configurations. Refine with filters or upvote what's useful.
This project is a community-driven knowledgebase and registry for AI agent configurations. It serves as a centralized repository for system prompts, environment settings, and integration strategies designed to standardize the behavior of various AI-assisted development tools. By capturing these configurations in a structured format, the project enables developers to maintain consistent AI agent performance across different workstations and environments. The repository distinguishes itself through a hierarchical, version-controlled architecture that treats prompt engineering patterns as portab
Organizes version-controlled system prompts and integration parameters specifically for Claude Code environments.
Caveman is a set of tools and configurations designed for large language model token optimization. It focuses on reducing the amount of data processed during AI interactions to lower costs and maximize the available context window. The project implements a fragmented communication style that replaces full grammatical sentences with concise technical keywords. This approach extends to AI context optimization by condensing memory files and tool descriptions, and includes a specialized configuration for generating terse, one-line code reviews and short conventional commit messages. The system i
Optimizes the Claude Code CLI experience by compressing tool descriptions and communication styles.
This project is an LLM research workflow framework and academic writing automation tool designed to coordinate the research, drafting, and peer-review processes of scholarly papers. It functions as a scientific manuscript auditor and an AI peer review system that uses multi-agent evaluation to verify citation integrity and score manuscripts against quality rubrics. The system distinguishes itself through a verification suite that employs vision models for figure fidelity auditing and anchor links for claim support verification. It includes a writing style calibration utility that analyzes pre
Manages a structured research to finalization process using Claude Code plugins and configurations.
huashu-design is a design system infrastructure and a set of specialized design engines for high-fidelity HTML prototyping, quality evaluation, and presentation conversion. It provides tools for generating interactive single-file HTML mockups, frame-based motion design, and a visual evaluator that analyzes design quality across five dimensions using radar charts. The system distinguishes itself through a translation pipeline that converts HTML slide decks into editable PowerPoint and PDF objects rather than flat images. It includes a motion design engine that uses a time-slice model to render
Provides a specialized skill for Claude Code to generate high-fidelity HTML prototypes, presentations, and animations.
Airweave is a unified AI knowledge base platform that syncs data from external APIs into a searchable layer for retrieval-augmented generation. It provides a pre-built data connector library and a framework for building custom connectors, enabling the extraction, transformation, and synchronization of structured and unstructured data from SaaS applications. The platform includes a hybrid vector retrieval system that combines semantic, neural, and keyword search strategies to deliver grounded context for AI agents. The platform distinguishes itself through an agentic search engine that iterati
Configures the MCP server to point at a self-managed instance using environment variables for local or Docker deployment.
xcodebuildmcp is a Model Context Protocol server that exposes Xcode build, test, and device management tools for AI coding agents to automate iOS and macOS development workflows. It operates as a background daemon per workspace, communicating tool requests and responses over standard input/output using JSON-RPC messages, and streams progress and results as newline-delimited JSON objects for machine parsing. The project provides an interactive setup wizard and file-based client configuration to install skill files into predefined directories for supported AI coding clients. It manages the full
Configures MCP servers across multiple AI coding clients with automated skill installation and client integration.
This is a curated gallery of real-world workflows demonstrating how to use Claude Code for AI-driven coding, debugging, and development automation. The showcase includes executable scripts that reproduce each AI interaction locally, allowing you to see exactly how the assistant generates, explains, and modifies code within a development environment. The project shows how to build custom AI agents with targeted prompts and multi-step slash commands, define project-wide memory that persists across sessions, and inject domain-specific knowledge through markdown files. It also demonstrates integr
Workflows for building custom AI agents, automating code review, and running continuous integration tasks with Claude Code.
This repository catalogs the system prompts used by Claude Code, organizing them into browsable categories with token-count estimates for each prompt. It functions as both a prompt library browser and a revision tracker, surfacing the size and complexity of individual prompts to support auditing and prompt engineering decisions. The project records prompt revisions by parsing git diffs between versions, capturing additions, removals, and token-count changes in a structured changelog. Token counts are approximated from character length using a fixed heuristic ratio, avoiding the need for API c
A browsable catalog of version-controlled system prompts used by Claude Code with token counts.
XcodeBuildMCP is a Model Context Protocol server and development tool bridge that provides AI agents with the ability to control xcodebuild, manage simulators, and automate the compilation and execution of Apple platform applications. It functions as a persistent daemon that proxies native IDE build and debug capabilities to external clients and agents. The project distinguishes itself by using the Model Context Protocol to expose build and device management tools through a standardized interface. It implements specialized skill priming and instruction configuration to ensure AI agents can in
Provides instructions for adding the MCP server configuration to Xcode's Claude Code agent settings.
mcp-context-forge is a Model Context Protocol federation gateway that unifies diverse AI tool servers and APIs into a single consistent interface for discovery and execution. It acts as a centralized proxy that aggregates multiple servers and APIs, allowing AI agents to access and invoke a unified set of tools, prompts, and resources. The project distinguishes itself through a multi-protocol translation bridge that converts communication between standard I/O, SSE, gRPC, and REST to enable interoperability between disparate tool servers. It includes a comprehensive LLM evaluation framework for
Connects external tool servers to a central gateway to enable unified discovery of available capabilities.
This project is an extension framework and orchestration system for Claude Code that uses lifecycle hooks to intercept and augment the execution flow of agents. It serves as a management layer for automating session startup, handling project context loading, and performing cleanup routines during AI coding sessions. The framework provides an orchestration system to spawn and manage specialized sub-agents with distinct prompts and toolsets to decompose complex technical tasks. It functions as a prompt engineering middleware to validate and inject context into user requests and as a tool guardr
Extends Claude Code by intercepting lifecycle events to automate workflows and enforce agent behaviors.
Tinker Cookbook is an open-source framework for fine-tuning large language models, supporting supervised learning, reinforcement learning, and parameter-efficient techniques like LoRA adapters. It provides a complete pipeline for aligning models with human preferences through multi-stage RLHF workflows, from supervised fine-tuning through preference optimization to reinforcement learning. The framework distinguishes itself through recipe-based training orchestration, where fine-tuning workflows are defined as composable recipe files that chain data loading, model configuration, and training l
Includes AI assistant skills that guide Claude Code to write training code and debug issues.
Provides reference configurations for documentation, development, and utility MCP servers.
Miroflow is an agent orchestration framework designed to coordinate multiple large language models and autonomous agents to perform complex research and reasoning tasks. It functions as a hierarchical workflow manager that distributes workloads across specialized agents using intent recognition and structured planning to gather deep information and solve challenging queries. The system distinguishes itself through a multi-model integration gateway and a provider-agnostic interface, allowing it to unify various language model providers. It extends these models via a tool-augmented framework th
Provides a structured sequence of intent recognition, planning, and delegation for the research-to-finalization lifecycle.