{"repo":"AMAP-ML/LongHorizon-Harness","free":true,"listed":false,"github":"https://github.com/AMAP-ML/LongHorizon-Harness","clone":"git clone https://github.com/AMAP-ML/LongHorizon-Harness.git","description":"The long-horizon computer-use harness. Run AI agents across desktop apps and the CLI for extended periods while preserving task state and making reliable progress on complex workflows. Features fresh-context execution, durable verified state, independent auditing, recoverable progress, and native Claude Code / Codex / OpenClaw integration.","language":"Python","stars":827,"topics":["agent","harness","long-horizon","long-horizon-agents","longhorizon-harness","claude","claude-code","claude-plugin","cli","codex"],"license":"MIT","category":"cli-tools","readme_excerpt":"LongHorizon-Harness Loop Engineering for Computer-Use Agents Give Claude Code, Codex, OpenCode, or DeepSeek Harness a goal once. Keep it working across desktop apps and the terminal for dozens of hours. Plan → act → verify → checkpoint or recover → repeat — until the work is actually done. Usage · The Loop · Computer Use · Results · Project Website · 简体中文 The model determines what an agent can do in one round. LongHorizon-Harness engineers the loop around it: what to do next, how to verify the result in the real computer, what progress to preserve, and how to continue after failure or context refresh. A Loop Engineering system for Claude Code, Codex, OpenCode, and DeepSeek Harness. One-command install, ready to run. LongHorizon-Harness turns existing agents into long-running computer-use systems. Across desktop apps and the terminal CLI, it continuously recovers the goal and verified state, selects the next bounded step, executes it with a fresh context, checks the actual result, and then checkpoints accepted progress or feeds failure evidence into the next round. It does not train a new model or replace an existing agent; it provides the durable execution loop around one. ✨ News - [v0.1.6 · 2026-08-15] Added OpenCode CLI support. LongHorizon-Harness can now run opencode run prompt as --agent opencode , with role-scoped read/write permissions, OpenCode API endpoint overrides, normalized JSON results, and CLI/config/doctor integration. The Web workbench can select OpenCode Har","default_branch":null,"files":null,"tree":[],"storefront":"/r/AMAP-ML","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AMAP-ML/LongHorizon-Harness/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}