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An agent harness is the low level executor for one prepared OpenClaw agent turn. It is not a model provider, not a channel, and not a tool registry. For the user-facing mental model, see Agent runtimes. Use this surface only for bundled or trusted native plugins. The contract is still experimental because the parameter types intentionally mirror the current embedded runner.

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When to use a harness

Register an agent harness when a model family has its own native session runtime and the normal OpenClaw provider transport is the wrong abstraction. Examples:
  • a native coding-agent server that owns threads and compaction
  • a local CLI or daemon that must stream native plan/reasoning/tool events
  • a model runtime that needs its own resume id in addition to the OpenClaw session transcript
Do not register a harness just to add a new LLM API. For normal HTTP or WebSocket model APIs, build a provider plugin.

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What core still owns

Before a harness is selected, OpenClaw has already resolved:
  • provider and model
  • runtime auth state
  • thinking level and context budget
  • the OpenClaw transcript/session file
  • workspace, sandbox, and tool policy
  • channel reply callbacks and streaming callbacks
  • model fallback and live model switching policy
That split is intentional. A harness runs a prepared attempt; it does not pick providers, replace channel delivery, or silently switch models. The prepared attempt also includes params.runtimePlan, an OpenClaw-owned policy bundle for runtime decisions that must stay shared across PI and native harnesses:
  • runtimePlan.tools.normalize(...) and runtimePlan.tools.logDiagnostics(...) for provider-aware tool schema policy
  • runtimePlan.transcript.resolvePolicy(...) for transcript sanitization and tool-call repair policy
  • runtimePlan.delivery.isSilentPayload(...) for shared NO_REPLY and media delivery suppression
  • runtimePlan.outcome.classifyRunResult(...) for model fallback classification
  • runtimePlan.observability for resolved provider/model/harness metadata
Harnesses may use the plan for decisions that need to match PI behavior, but should still treat it as host-owned attempt state. Do not mutate it or use it to switch providers/models inside a turn.

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Register a harness

Import: openclaw/plugin-sdk/agent-harness 
import type { AgentHarness } from "openclaw/plugin-sdk/agent-harness";
import { definePluginEntry } from "openclaw/plugin-sdk/plugin-entry";

const myHarness: AgentHarness = {
  id: "my-harness",
  label: "My native agent harness",

  supports(ctx) {
    return ctx.provider === "my-provider"
      ? { supported: true, priority: 100 }
      : { supported: false };
  },

  async runAttempt(params) {
    // Start or resume your native thread.
    // Use params.prompt, params.tools, params.images, params.onPartialReply,
    // params.onAgentEvent, and the other prepared attempt fields.
    return await runMyNativeTurn(params);
  },
};

export default definePluginEntry({
  id: "my-native-agent",
  name: "My Native Agent",
  description: "Runs selected models through a native agent daemon.",
  register(api) {
    api.registerAgentHarness(myHarness);
  },
});

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Selection policy

OpenClaw chooses a harness after provider/model resolution:
  1. Model-scoped runtime policy wins.
  2. Provider-scoped runtime policy comes next.
  3. auto asks registered harnesses if they support the resolved provider/model.
  4. If no registered harness matches, OpenClaw uses PI unless PI fallback is disabled.
Plugin harness failures surface as run failures. In auto mode, PI fallback is only used when no registered plugin harness supports the resolved provider/model. Once a plugin harness has claimed a run, OpenClaw does not replay that same turn through PI because that can change auth/runtime semantics or duplicate side effects. Whole-session and whole-agent runtime pins are ignored by selection. That includes stale session agentHarnessId values, agents.defaults.agentRuntime, agents.list[].agentRuntime, and OPENCLAW_AGENT_RUNTIME. /status shows the effective runtime selected from the provider/model route. If the selected harness is surprising, enable agents/harness debug logging and inspect the gateway’s structured agent harness selected record. It includes the selected harness id, selection reason, runtime/fallback policy, and, in auto mode, each plugin candidate’s support result. The bundled Codex plugin registers codex as its harness id. Core treats that as an ordinary plugin harness id; Codex-specific aliases belong in the plugin or operator config, not in the shared runtime selector.

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Provider plus harness pairing

Most harnesses should also register a provider. The provider makes model refs, auth status, model metadata, and /model selection visible to the rest of OpenClaw. The harness then claims that provider in supports(...). The bundled Codex plugin follows this pattern:
  • preferred user model refs: openai/gpt-5.5
  • compatibility refs: legacy codex/gpt-* refs remain accepted, but new configs should not use them as normal provider/model refs
  • harness id: codex
  • auth: synthetic provider availability, because the Codex harness owns the native Codex login/session
  • app-server request: OpenClaw sends the bare model id to Codex and lets the harness talk to the native app-server protocol
The Codex plugin is additive. Plain openai/gpt-* agent refs on the official OpenAI provider select the Codex harness by default. Older codex/gpt-* refs still select the Codex provider and harness for compatibility. For operator setup, model prefix examples, and Codex-only configs, see Codex Harness. OpenClaw requires Codex app-server 0.125.0 or newer. The Codex plugin checks the app-server initialize handshake and blocks older or unversioned servers so OpenClaw only runs against the protocol surface it has been tested with. The 0.125.0 floor includes the native MCP hook payload support that landed in Codex 0.124.0, while pinning OpenClaw to the newer tested stable line.

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Tool-result middleware

Bundled plugins can attach runtime-neutral tool-result middleware through api.registerAgentToolResultMiddleware(...) when their manifest declares the targeted runtime ids in contracts.agentToolResultMiddleware. This trusted seam is for async tool-result transforms that must run before PI or Codex feeds tool output back into the model. Legacy bundled plugins can still use api.registerCodexAppServerExtensionFactory(...) for Codex app-server-only middleware, but new result transforms should use the runtime-neutral API. The Pi-only api.registerEmbeddedExtensionFactory(...) hook has been removed; Pi tool-result transforms must use runtime-neutral middleware.

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Terminal outcome classification

Native harnesses that own their own protocol projection can use classifyAgentHarnessTerminalOutcome(...) from openclaw/plugin-sdk/agent-harness-runtime when a completed turn produced no visible assistant text. The helper returns empty, reasoning-only, or planning-only so OpenClaw’s fallback policy can decide whether to retry on a different model. It intentionally leaves prompt errors, in-flight turns, and intentional silent replies such as NO_REPLY unclassified.

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Native Codex harness mode

The bundled codex harness is the native Codex mode for embedded OpenClaw agent turns. Enable the bundled codex plugin first, and include codex in plugins.allow if your config uses a restrictive allowlist. Native app-server configs should use openai/gpt-*; OpenAI agent turns select the Codex harness by default. Legacy openai-codex/* routes should be repaired with openclaw doctor --fix, and legacy codex/* model refs remain compatibility aliases for the native harness. When this mode runs, Codex owns the native thread id, resume behavior, compaction, and app-server execution. OpenClaw still owns the chat channel, visible transcript mirror, tool policy, approvals, media delivery, and session selection. Use provider/model agentRuntime.id: "codex" when you need to prove that only the Codex app-server path can claim the run. Explicit plugin runtimes fail closed; Codex app-server selection failures and runtime failures are not retried through PI.

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Runtime strictness

By default, OpenClaw uses auto provider/model runtime policy: registered plugin harnesses can claim a provider/model pair, and PI handles the turn when none match. OpenAI agent refs on the official OpenAI provider default to Codex. Use an explicit provider/model plugin runtime such as agentRuntime.id: "codex" when missing harness selection should fail instead of routing through PI. Selected plugin harness failures always fail hard. This does not block an explicit provider/model agentRuntime.id: "pi". For Codex-only embedded runs: 
{
  "models": {
    "providers": {
      "openai": {
        "agentRuntime": {
          "id": "codex"
        }
      }
    }
  },
  "agents": {
    "defaults": {
      "model": "openai/gpt-5.5"
    }
  }
}
If you want a CLI backend for one canonical model, put the runtime on that model entry: 
{
  "agents": {
    "defaults": {
      "model": "anthropic/claude-opus-4-7",
      "models": {
        "anthropic/claude-opus-4-7": {
          "agentRuntime": {
            "id": "claude-cli"
          }
        }
      }
    }
  }
}
Per-agent overrides use the same model-scoped shape: 
{
  "agents": {
    "list": [
      {
        "id": "codex-only",
        "model": "openai/gpt-5.5",
        "models": {
          "openai/gpt-5.5": {
            "agentRuntime": { "id": "codex" }
          }
        }
      }
    ]
  }
}
Legacy whole-agent runtime examples like this are ignored: 
{
  "agents": {
    "defaults": {
      "agentRuntime": {
        "id": "codex"
      }
    }
  }
}
With an explicit plugin runtime, a session fails early when the requested harness is not registered, does not support the resolved provider/model, or fails before producing turn side effects. That is intentional for Codex-only deployments and for live tests that must prove the Codex app-server path is actually in use. This setting only controls the embedded agent harness. It does not disable image, video, music, TTS, PDF, or other provider-specific model routing.

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Native sessions and transcript mirror

A harness may keep a native session id, thread id, or daemon-side resume token. Keep that binding explicitly associated with the OpenClaw session, and keep mirroring user-visible assistant/tool output into the OpenClaw transcript. The OpenClaw transcript remains the compatibility layer for:
  • channel-visible session history
  • transcript search and indexing
  • switching back to the built-in PI harness on a later turn
  • generic /new, /reset, and session deletion behavior
If your harness stores a sidecar binding, implement reset(...) so OpenClaw can clear it when the owning OpenClaw session is reset.

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Tool and media results

Core constructs the OpenClaw tool list and passes it into the prepared attempt. When a harness executes a dynamic tool call, return the tool result back through the harness result shape instead of sending channel media yourself. This keeps text, image, video, music, TTS, approval, and messaging-tool outputs on the same delivery path as PI-backed runs.

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Current limitations

  • The public import path is generic, but some attempt/result type aliases still carry Pi names for compatibility.
  • Third-party harness installation is experimental. Prefer provider plugins until you need a native session runtime.
  • Harness switching is supported across turns. Do not switch harnesses in the middle of a turn after native tools, approvals, assistant text, or message sends have started.