HarnessRouter

A model reasons and generates output. An agent harness is the runtime that turns that output into completed work through an execution loop, tools, session state, files, and a working environment. GPT-5.5 and Claude Fable 5 are models. Codex, Claude Code, and Hermes are agent harnesses.

Yes. Codex, Claude Code, Hermes, and similar agent harnesses are complete agent runtimes, not only developer tools. HarnessRouter runs them behind one API, while the Unified Harness Protocol (UHP) defines the shared contract your agent product uses to select, configure, and drive each harness. Their execution loops, tools, Sessions, file handling, and task capabilities can power features inside your agent product, while you keep your own interface, authentication, permissions, data, and user experience.

Model choice is only half of the configuration. Even with the same model, the harness can change the agent loop, tool use, token consumption, latency, reliability, and cost. HarnessRouter lets you benchmark harness and model combinations on your own tasks, then route each workload to the combination that fits your quality, speed, and cost targets without rebuilding the product integration. You do not need to run every harness at the same time.

No. A model router selects models and returns model output. HarnessRouter runs complete agent harnesses that use models, tools, files, and execution loops to perform tasks and return finished work. The two layers solve different problems and can be used together.

You can use them directly to build an agent demo. Turning that demo into a product your users can rely on also requires isolated sandboxes, sessions, streaming, files, cancellation, recovery, scaling, and observability. HarnessRouter provides this production runtime through one API.

You can build any agent product whose core work can be expressed as tasks for a supported harness. Examples include personal agents, codebase fixer agents, research agents, contract review agents, financial agents, data analysis agents, presentation agents, spreadsheet agents, dashboard agents, and video agents. In just a few hours, we launched a personal agent product inspired by Grok DOT, with agent reasoning, tools, file handling, and task execution running behind the agent product interface.

The Unified Harness Protocol is an open and versioned standard for connecting applications to complete agent harnesses. It defines a shared contract for selecting and configuring harnesses, running tasks, streaming progress, continuing Sessions, exchanging files, cancelling work, handling errors, and receiving results. Its task surface is compatible with the relevant OpenAI Responses API surface, and it can be implemented independently of HarnessRouter Cloud.

Yes. Your agent product keeps the same HarnessRouter API when it selects a different configured harness for a new task or Session. Each harness still has its own capabilities, tools, and behavior. A continued Session remains on the configured harness that started it.

Your application can receive streamed progress and events, task and Session status, generated files and artifacts, the final result, structured errors, and execution traces. It can also continue a Session, cancel running work, and retrieve the files produced by the agent.

Community Edition is the Apache 2.0 reference implementation that you run on infrastructure you control. It packages the Console, Gateway, and Runner in one Docker deployment and uses your own model provider credentials. HarnessRouter Cloud is the managed service. HarnessRouter operates and maintains the runtime, provisions isolated sandboxes for tasks, supports execution tracing, and scales execution for you. Both editions implement the same UHP contract.