Multi-agent orchestrator for autonomous software development
The self-improving agentic harness for Claude Code. Coding agents harness LLMs — but who harnesses the coding agents?
Deep Agents - a library for building controllable AI agents with LangGraph
Opinionated OpenCode agent harness — PRIME, plan, build, QA, skills, MCP wiring, hashline editing.
No description provided.
No description provided.
Harness-backed AI testing on top of Vitest.
Solo-dev harness engineering kit for Claude Code, with experimental Codex and Kiro CLI runtime rendering.
Give AI agents full access to the Harness.io platform — manage pipelines, deployments, cloud costs, chaos engineering, feature flags, SEI, and 125+ resource types through 11 MCP tools
Company-style AI agent harness for Claude and Codex. Installs commands, CXX agents, skills, HR-Resource hiring pool, and project-local .harness runtime state.
Stable application runtime and operator control plane for agent workspaces.
A transactional execution harness for AI coding agents with evidence-backed reports.
No description provided.
OpenClaw ACP runtime backend with plugin-owned session and transport management.
Native UI testing module for React Native Harness.
CLI scaffolding for multi-agent harness systems
A local PTY harness that wraps terminal AI agents (Claude, Codex, Pi) and adds a control plane for discovery, messaging, and coordination.
RubyPi is a minimal, composable AI agent harness for Ruby. Build production-ready LLM agents and AI agents with a unified provider interface across OpenAI, Anthropic Claude, and Google Gemini, plus first-class support for tool calling (function calling), streaming responses, automatic retries, provider fallback, context compaction, and a think-act-observe agent loop. Anti-framework design — small, idiomatic, and explicit. Ideal for building autonomous AI agents, ReAct agents, tool-using LLM agents, and chatbots in Ruby.
No description provided.
No description provided.