Build your own network of agents from Claude Code, Codex and Pi: persistent teams with roles, shared context and owned work.
Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Your coding agent for controlled development in the workspace you lead. A Pi-native shell with Organic Driven Development, focused subagents, risk-based native review, live changes and agent views, and permission modes that keep destructive guards.
an open-source alternative to the dots, bots and muses of the world, run an office of claude code/codex like agents on your laptop, sandboxes or anywhere, uses your existing subscriptions
The ultimate harness for coding agents and beyond. All your agents. All your machines. One command center. Start with code, then follow your curiosity and build across disciplines: CAD, circuits, robots, games and music.
OpenLIT is the open-source agent harness engineering platform: trace, evaluate, guard, and improve everything around the model in your AI agents, on OTEL.
AI coding harness for desktop, terminal and CI. Maps your repo, edits code by symbol through AST and LSP, then runs your checks. Any model or the plan you already pay for. Get it at https://empryo.com
A specialist team for the coding agent you already use: 12 roles, 21 workflows and 33 skills that plan, build in parallel, review and debug, leaving plans, ADRs and results as files. Gates wait for your own tests. Also research, slides and video. One .agents/ folder for Claude Code, Codex, Cursor and 11 more.
开源 · 本地优先的 AI 智能体:编程与实干兼备。 自带模型密钥,内置 MCP、技能、插件、工作流、知识库以及数据库。
The Agent Harness for AI-Human Collaboration, inspired by the AI-DLC (AI-Driven Development Lifecycle)
🛠️ The meta-harness for AI agents — scaffold your own focused, branded agent harness with its own npx CLI, MCP server, memory, learning loop, and witness-signed releases. Works with Claude Code, Codex, pi.dev, Hermes, OpenClaw, and RVM (hardware-isolated sandbox).
Observability and enforcement for AI agent harnesses. Capture every run and runtime reliability with policy enforcement.
Full-stack AI agent for coding, files, terminals, tools, research, content, multimodal work, and multi-agent workflows.
Open-source room for humans + cross-vendor AI agents. Every agent gets its own name, memory, skills, and workstation. Any runtime, your infra — no per-agent fees.
天枢harness是一个的终端编程智能体,它要回答的核心问题是:模型何以稳定地交付——目标不漂移、完成有证据、验证有闭环,不说"应该修好了"。为此它在模型与真实世界之间建立一层认知执行环境(CVM),把目标、状态、证据、资源、权限与终止条件从对话历史中外部化,由运行时持续管理。同时对deepseek v4极度优化。
The operational superset of Pi Coding Agent — everything Pi, plus observability, governance, recovery, evaluation and multi-agent orchestration. Pi Coding Agent 的运维超集——完整继承 Pi 的核心能力,并进一步扩展可观测性、治理、故障恢复、评估和多 Agent 编排。
Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.
mu (μ): a coding agent that thinks before it acts. A small, fast judge makes the routine calls, the big model does the work. Built on pi and AionUi.
Gear (General Evolution Architecture) is RSI infrastructure for AI agents. Use Gear to refine agent harnesses.
Claude Code-style auto-memory plugin for DeepSeek Harness (dsh): typed memory files + MEMORY.md index auto-injected into the system prompt. File-only, no external services.
Durable single-Agent Harness for TypeScript: recoverable Threads, context continuity, explicit side effects, and a native TUI.
A coding agent harness built specifically for Motif-3
USL is the storage-first reference implementation of the Agent Session Protocol (ASP). ACP handles the live present (editor↔agent interaction); ASP handles the durable past and cross-runtime migration; USL is the storage engine behind ASP.
Pi adapter for official DeepSeek Harness minimal mode. V4 Pro thinks We need… / I need…, not Let me…
Nausicaa treats an Agent run as a dynamic topology of Lanes rather than one fixed linear loop. The model can decide when to observe, fan out, delegate, or collaborate across Runs; the Host keeps identity, permissions, durability, and recovery as explicit facts.
A custom coding harness for TypeSafe AI's Jev: an LLM proposes, Jev answers narrow questions, code decides, every step leaves a receipt.
⚡ Millisecond System-1 judgement for every tool call in DeepSeek Harness — Jev-powered risk classification & evidence-gated auto-approval. Fail-closed by construction. dsh 生态第一个 System-1 决策插件