Projects sharing features with Ccpm

vibe-vibe is an LLM agent engineering framework and toolchain optimizer designed for orchestrating multi-agent systems. It serves as a comprehensive guide and methodology for transforming conceptual ideas into deployed applications through agentic software engineering. The project focuses on the orchestration of specialized AI agent roles with defined collaboration boundaries and iterative feedback loops. It provides frameworks for toolchain optimization, including the selection and evaluation of protocols that extend model capabilities and the design of standardized tool interfaces. The sys

This project is an AI agent workflow orchestrator and software development framework designed to transform high-level feature descriptions into executable implementation steps for AI assistants. It provides a structured system of prompt templates that guides large language models through the transition from product drafting to technical planning and code execution. The framework focuses on a methodology for decomposing product blueprints into sequenced lists of technical sub-tasks. It employs a system of prompt engineering to standardize outputs, ensuring that abstract requirements are conver

This project is an LLM coding agent orchestrator and AI software engineering platform designed to manage fleets of agents that autonomously solve issues, handle pull requests, and fix CI failures. It functions as an agentic CI/CD automator and parallel workflow manager, coordinating the end-to-end development lifecycle from initial ticket tracking to final code merging. The system is distinguished by its modular plugin framework and isolated worktree management, which allow multiple agents to work on separate coding tasks simultaneously without file system conflicts. It utilizes role-based mo

This project is an AI agent workflow framework and development toolkit designed for AI-driven software engineering. It provides a system of modular instructions, prompt libraries, and standardized routines to orchestrate complex engineering sequences and automate the decomposition of plans into technical tasks. The system differentiates itself through advanced context management and prompt engineering, using state compression and handoff documents to preserve conversation history between different AI sessions. It employs a structured library of prompt skills and high-signal trigger words to e

jcode is a framework for developing autonomous AI coding agents that automate software development tasks. It functions as an agent orchestrator, tool runtime, and semantic memory engine, enabling the creation of agents that can modify code, run tests, and iterate on their own functionality. The project is distinguished by its use of recursive agent swarming, where a hierarchy of collaborating agents can spawn child agents to decompose complex tasks. It implements a semantic memory system that combines vector-based retrieval with graph-based relationship mapping to maintain context across sess

Pentagi is an autonomous security testing framework and agent orchestrator designed to plan and execute end-to-end security assessments. It utilizes a coordination engine to decompose complex goals into actionable subtasks, performing automated penetration testing and vulnerability research within isolated container environments. The system distinguishes itself through a temporal knowledge graph that tracks semantic relationships between entities and vulnerabilities to reuse intelligence across projects. It includes a web intelligence reconnaissance tool for automated data gathering and agent

oh-my-pi is an agentic workflow automation platform and AI coding agent orchestrator designed for autonomous software engineering. It functions as a multi-model LLM router and an LSP-integrated development environment, coordinating specialized AI agents to perform codebase analysis, automated refactoring, and complex task execution. The system distinguishes itself through the use of subagent coordination to execute parallel tasks within isolated environments and an auto-research framework for iterative experiments. It employs AST-driven structural search for code discovery and content-hash an

OpenDevin is an autonomous software engineering agent and orchestrator designed to execute coding tasks and manage development workflows using large language models. It functions as a centralized control center for managing and switching between various local and cloud artificial intelligence backends. The system utilizes a Docker sandbox environment to isolate autonomous agents in containers, protecting the host filesystem during code execution. It includes an automated engineering workflow tool that integrates with version control and chat services to trigger tasks via webhooks or scheduled

Gastown is an LLM agent orchestration platform designed to coordinate multiple AI agents with persistent state and context recovery across coding tasks. It provides a coordination layer that manages agent lifecycles, monitors health through a real-time dashboard, and ensures continuity during task executions. The system distinguishes itself through a federated agent network that links separate orchestration instances to distribute work and track agent reputation. It employs a git-backed work state manager that uses version control worktrees to store progress as structured data and a bisecting

Agent-skills is a collection of structured instructions and behavioral personas designed to standardize how AI coding agents perform engineering tasks. It functions as a workflow orchestrator that maps natural language intent to repeatable technical sequences and verification checklists. The project distinguishes itself through the use of specialized markdown-defined roles, such as security auditors or test engineers, to apply targeted domain expertise. It employs an evidence-based verification model that requires runtime data or passing tests as mandatory exit criteria to ensure AI-generated

Antigravity-kit is a multi-agent orchestrator and routing engine designed to coordinate specialized large language model agents. It functions as a conversational workflow automation tool and a context management system that executes complex tasks through a chat interface. The system utilizes a routing engine to classify user requests and dispatch them to domain-expert agents. It employs a multi-agent orchestration model that allows specialist workers to operate in parallel and combine their outputs. To manage operational efficiency, the kit includes a memory layer for storing project convent

CodeWhale is an AI coding agent orchestrator and development harness designed to coordinate autonomous agents that read, edit, and verify code. It provides a secure environment for AI agents to perform multi-step software engineering tasks, utilizing a sandboxed execution model to isolate shell commands and protect the host system. The system distinguishes itself by spawning multiple independent agents in parallel to handle separate investigation or implementation slices simultaneously. It employs a multi-model gateway to route requests across various cloud APIs and local servers, and utilize

Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software engineer. It parses repositories into a structured code knowledge graph, enabling AI agents to perform multi-hop reasoning, dependency tracing, and grounded technical analysis across large codebases. The system distinguishes itself through a spec-driven development framework where agents generate detailed technical specifications and architecture plans before implementing multi-file code changes. It utilizes a durable execution engine to coordinate specialized AI personas for

Claude Squad is a terminal-based orchestrator for running multiple AI coding assistants in parallel. It manages the lifecycle of AI agent sessions from a single keyboard-driven interface, allowing users to launch, monitor, pause, resume, and terminate agents without leaving the command line. The tool isolates each agent's work in separate git worktrees, so changes remain on independent branches and never interfere with each other. Before any modifications are committed or pushed, users can review a diff preview of what each agent produced and approve or reject the changes. This diff-based app

Backlog.md is a local-first project tracker and Markdown task manager that stores project data as plain text files in a local folder. It functions as a command-line interface tool for creating and organizing tasks and as a Kanban board visualizer that renders these task lists into interactive web and terminal interfaces. The project serves as an AI agent workflow orchestrator, providing a protocol that allows AI assistants to decompose high-level ideas into actionable tasks and implementation plans. It ensures a standardized definition of done by automatically applying reusable, project-wide

This project is a suite of tools for autonomous engineering, featuring a workflow manager that chains ideation, planning, and implementation into a single automated process for delivering pull requests. It includes a technical implementation planner for codebase research and blueprint generation, along with a framework for agentic code review that uses specialized agents to identify security and architectural issues. The system provides utilities for AI coding assistant migration, including a plugin converter for transforming instructions between different IDEs and a configuration synchronize

Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

AIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations

This project is an autonomous software development assistant and project management tool that utilizes a multi-agent orchestrator to automate complex workflows. It functions as an agentic framework designed to research, plan, execute, and verify software development tasks by coordinating specialized agents that manage context windows and system performance. The system distinguishes itself through a structured, interview-based requirement engineering phase that clarifies project objectives before initiating automated work. It employs atomic task decomposition to break goals into independent un

This project is an autonomous AI software engineering orchestrator and development loop manager. It implements a system for managing AI coding agents that execute iterative development cycles, processing technical requirements through a persistent task queue based on priority and dependencies. The system synchronizes development progress with GitHub by converting issues and comments into actionable plans and automating pull requests and status updates. It provides a secure execution layer by running coding operations within an isolated sandbox environment to protect the host file system. To

gstack is an AI agent framework and development workflow system designed to automate the software development lifecycle. It coordinates specialized AI personas to manage tasks across product design, engineering management, and quality assurance, transforming product intent into technical specifications and final releases. The project is distinguished by its deep integration of headless browser automation and semantic code memory. It utilizes a persistent Chromium daemon for web scraping and visual auditing, and implements a searchable knowledge base that logs architectural decisions and repos

This project is a command line interface and GitHub CLI extension that functions as an AI coding agent and model orchestrator. It enables the writing of code and the management of repositories through natural language prompts using large language models. The tool implements the Agent Client Protocol to act as a standardized agent server for external editors. It features a provider-agnostic routing system that allows switching between different hosted AI models or external compatible endpoints. Capabilities include the automation of Git workflows, such as managing pull requests and issues, an

CAI is a framework for building autonomous security agents and an orchestration system for coordinating multiple specialized agents. It functions as an agentic workflow engine and an autonomous cyber-defense tool that maps language model reasoning to security kill chain functions for threat detection and mitigation. The system distinguishes itself through multi-agent coordination patterns, such as swarms and hierarchies, and the use of stateful conversation handoffs. It implements multi-layer input and output guardrails to block prompt injections and validate commands before they reach the sy

Refact is an autonomous AI software engineering system and code assistant. It functions as an agent orchestrator capable of planning, executing, and managing multi-step development workflows to complete complex software tasks independently. The system distinguishes itself through agentic state management, using isolated worktrees and versioned checkpoints to allow autonomous agents to experiment with code changes and roll back to stable states if tasks fail. It further extends its capabilities via the Model Context Protocol, connecting the AI engine to external databases, version control syst

CodexMonitor is an AI agent orchestration interface designed for monitoring agentic workflows and managing remote daemon connections. It provides a web-based dashboard for coordinating AI agents across local workspaces and managing the execution of large language model tasks. The system distinguishes itself by integrating AI agents directly into git-based development workflows, synchronizing GitHub issues and pull requests with conversation threads. It uses branch worktree isolation to run tasks in separate physical directory copies, preventing state leakage between concurrent agent activitie

GenericAgent is an LLM agent framework and autonomous system controller designed to manage local systems, web browsers, and hardware interfaces through action and observation loops. It functions as a tool orchestrator that routes model calls to local executors, enabling the automation of complex tasks on a host machine. The project is distinguished by its self-evolving AI agent capabilities, which convert successful execution paths into reusable procedural scripts and skill trees to reduce future reasoning overhead. It employs a context optimization engine that utilizes layered memory hierarc

This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ