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An agent runtime is the component that owns one prepared model loop: it receives the prompt, drives model output, handles native tool calls, and returns the finished turn to OpenClaw. Runtimes are easy to confuse with providers because both show up near model configuration. They are different layers:
LayerExamplesWhat It Means
Provideropenai, anthropic, openai-codexHow OpenClaw authenticates, discovers models, and names model refs.
Modelgpt-5.5, claude-opus-4-6The model selected for the agent turn.
Agent runtimepi, codex, ACP-backed runtimesThe low level loop that executes the prepared turn.
ChannelTelegram, Discord, Slack, WhatsAppWhere messages enter and leave OpenClaw.
You will also see the word harness in code and config. A harness is the implementation that provides an agent runtime. For example, the bundled Codex harness implements the codex runtime. The config key is still named embeddedHarness for compatibility, but user-facing docs and status output should generally say runtime. The common Codex setup uses the openai provider with the codex runtime: 
{
  agents: {
    defaults: {
      model: "openai/gpt-5.5",
      embeddedHarness: {
        runtime: "codex",
      },
    },
  },
}
That means OpenClaw selects an OpenAI model ref, then asks the Codex app-server runtime to run the embedded agent turn. It does not mean the channel, model provider catalog, or OpenClaw session store becomes Codex. For the OpenAI-family prefix split, see OpenAI and Model providers. For the Codex runtime support contract, see Codex harness.

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Runtime ownership

Different runtimes own different amounts of the loop.
SurfaceOpenClaw PI embeddedCodex app-server
Model loop ownerOpenClaw through the PI embedded runnerCodex app-server
Canonical thread stateOpenClaw transcriptCodex thread, plus OpenClaw transcript mirror
OpenClaw dynamic toolsNative OpenClaw tool loopBridged through the Codex adapter
Native shell and file toolsPI/OpenClaw pathCodex-native tools, bridged through native hooks where supported
Context engineNative OpenClaw context assemblyOpenClaw projects assembled context into the Codex turn
CompactionOpenClaw or selected context engineCodex-native compaction, with OpenClaw notifications and mirror maintenance
Channel deliveryOpenClawOpenClaw
This ownership split is the main design rule:
  • If OpenClaw owns the surface, OpenClaw can provide normal plugin hook behavior.
  • If the native runtime owns the surface, OpenClaw needs runtime events or native hooks.
  • If the native runtime owns canonical thread state, OpenClaw should mirror and project context, not rewrite unsupported internals.

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Runtime selection

OpenClaw chooses an embedded runtime after provider and model resolution:
  1. A session’s recorded runtime wins. Config changes do not hot-switch an existing transcript to a different native thread system.
  2. OPENCLAW_AGENT_RUNTIME=<id> forces that runtime for new or reset sessions.
  3. agents.defaults.embeddedHarness.runtime or agents.list[].embeddedHarness.runtime can set auto, pi, or a registered runtime id such as codex.
  4. In auto mode, registered plugin runtimes can claim supported provider/model pairs.
  5. If no runtime claims a turn in auto mode and fallback: "pi" is set (the default), OpenClaw uses PI as the compatibility fallback. Set fallback: "none" to make unmatched auto-mode selection fail instead.
Explicit plugin runtimes fail closed by default. For example, runtime: "codex" means Codex or a clear selection error unless you set fallback: "pi" in the same override scope. A runtime override does not inherit a broader fallback setting, so an agent-level runtime: "codex" is not silently routed back to PI just because defaults used fallback: "pi".

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Compatibility contract

When a runtime is not PI, it should document what OpenClaw surfaces it supports. Use this shape for runtime docs:
QuestionWhy It Matters
Who owns the model loop?Determines where retries, tool continuation, and final answer decisions happen.
Who owns canonical thread history?Determines whether OpenClaw can edit history or only mirror it.
Do OpenClaw dynamic tools work?Messaging, sessions, cron, and OpenClaw-owned tools rely on this.
Do dynamic tool hooks work?Plugins expect before_tool_call, after_tool_call, and middleware around OpenClaw-owned tools.
Do native tool hooks work?Shell, patch, and runtime-owned tools need native hook support for policy and observation.
Does the context engine lifecycle run?Memory and context plugins depend on assemble, ingest, after-turn, and compaction lifecycle.
What compaction data is exposed?Some plugins only need notifications, while others need kept/dropped metadata.
What is intentionally unsupported?Users should not assume PI equivalence where the native runtime owns more state.
The Codex runtime support contract is documented in Codex harness.

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Status labels

Status output may show both Execution and Runtime labels. Read them as diagnostics, not as provider names.
  • A model ref such as openai/gpt-5.5 tells you the selected provider/model.
  • A runtime id such as codex tells you which loop is executing the turn.
  • A channel label such as Telegram or Discord tells you where the conversation is happening.
If a session still shows PI after changing runtime config, start a new session with /new or clear the current one with /reset. Existing sessions keep their recorded runtime so a transcript is not replayed through two incompatible native session systems.