# Code Mode configuration > Code Mode configuration fields, automatic per-model activation, and the activation order - 网址：https://funcoding.ai/agents/openclaw/tools/code-mode/configuration/ - 来源：OpenClaw 官方文档原文（英文），MIT 许可，同步于 2026-10-11 - 官方原文：https://docs.openclaw.ai/zh-CN/tools/code-mode/configuration --- ## Configuration An absent global `tools.codeMode` setting defaults to `"auto"`. If you author a Code Mode object, its activation stays off unless that object explicitly sets `enabled`; this lets you stage executor or limit settings without enabling the feature. Shorthand `false` also disables it. Agent and model overrides retain their existing precedence. | Field | Default | Clamp | | --------------------- | ---------- | ----------------------------------------------- | | `enabled` | See above | `false`, `true`, or `"auto"` (per-model) | | `executor` | `"node"` | `"node"` or `"quickjs"` | | `mode` | `"only"` | exposes control/direct tools, catalogs the rest | | `timeoutMs` | `10000` | `100`-`60000` | | `memoryLimitBytes` | `67108864` | `1048576`-`1073741824` | | `maxOutputBytes` | `65536` | `1024`-`10485760` | | `maxSnapshotBytes` | `10485760` | `1024`-`268435456` | | `maxPendingToolCalls` | `16` | `1`-`128` | | `snapshotTtlSeconds` | `900` | `1`-`86400` | | `searchDefaultLimit` | `8` | clamped to `maxSearchLimit` | | `maxSearchLimit` | `50` | `1`-`50` | Code Mode executes JavaScript only. Doctor and eligible Gateway startup migrations remove the retired `languages` setting from global and per-agent Code Mode config, preserving activation and limits. The default Node executor uses `node:vm` for trusted execution, not security isolation. Select `executor: "quickjs"` for the bundled hardened guest runtime. Agent-level executor settings override the global selection. See [Code Mode executors](https://funcoding.ai/agents/openclaw/tools/code-mode/executors/) for security, memory, wait, and upgrade behavior. `maxSnapshotBytes` caps QuickJS VM snapshots and the shared saved-result allowance; it does not cap Node's retained live context. `timeoutMs` is a wall-clock budget per `exec` or `wait` call. Worker preparation, guest computation, and inline tool waits share that budget; approval waits pause it. For an explicitly `awaitResults: true` cell, off-VM tool waiting also pauses the execution allowance. The same unused allowance resumes after settlement; worker preparation and guest execution never receive a fresh budget. Existing agent-run and tool deadlines continue running during required waits. The model-facing `exec` description includes the effective limit. Blocking guest computation that exhausts the budget fails with `timeout`. Unfinished tool calls can instead return `waiting`, so a later `wait` can resume them with a fresh call budget. Headless continuations also honor the exact worker-admission budget after queueing and initialization, alongside their configured slice limit and single headless wall-clock deadline. A checkpoint does not reset that wall deadline. When the shell `exec` tool is available, use it for heavier computation and keep guest JavaScript focused on coordinating tools and processing results. If code mode is enabled but the selected executor cannot load, OpenClaw fails closed for that run; it does not silently expose normal tools as a fallback. This holds for `true` and for `"auto"` runs where the model resolves as preferred: an engaged run never silently falls back to another executor or broad direct tool exposure. ## Automatic per-model activation `tools.codeMode.enabled` accepts three values: - `false`: code mode is off unless an agent or model override enables it. - `true`: code mode engages for tool-capable runs unless an override disables it. - `"auto"`: code mode engages only when the run's model is flagged as a preferred code-mode performer in its provider catalog. When the global setting is completely absent, OpenClaw behaves as if it were `"auto"`. An authored object without `enabled` behaves as `false`. These values supply the default when no agent or model override takes precedence. `"auto"` uses catalog capability; an explicit per-model boolean bypasses that capability preference. ### The `compat.codeMode` catalog flag Provider catalogs can tier a model with `compat.codeMode` on its model entry, next to flags like `compat.supportsTools`: - `"preferred"`: the model reliably writes short orchestration programs and benefits from the compact code-mode surface; `"auto"` engages code mode. - `"capable"` (or absent): the model can run code mode when forced with `enabled: true`, but `"auto"` keeps normal tool exposure. Models without tool support cannot use code mode at all; there is no separate "unsupported" tier. The flag is capability metadata owned by the provider plugin's catalog; core only reads the generic compat field. ### Shipped preferred models Bundled provider catalogs currently flag these models as `"preferred"`: | Provider | Models | | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- | | anthropic | `claude-fable-5`, `claude-opus-5-5`, `claude-opus-5`, `claude-sonnet-5`, `claude-mythos-5`, `claude-opus-4-8` | | deepseek | `deepseek-v4-pro`, `deepseek-v4-flash` | | google | `gemini-3-flash-preview`, `gemini-3.1-pro-preview`, `gemini-3.1-flash-lite`, `gemini-3.5-flash`, `gemini-3.5-flash-lite`, `gemini-3.6-flash`, `gemini-3.7-flash` | | kimi | `k3`, `k3-256k` | | minimax | `MiniMax-M3` | | moonshot | `kimi-k3` | | openai | `gpt-5.6`, `gpt-5.6-sol`, `gpt-5.6-terra`, `gpt-5.6-luna`, `gpt-5.5`, `gpt-5.5-pro` | | xiaomi | `mimo-v2.6-pro`, `mimo-v2.6-flash` | | zai | `glm-5.3`, `glm-5.2`, `glm-5.1` | `claude-haiku-4-5` is marked `"capable"`: it remains available through an explicit `true` agent or model setting, but `"auto"` does not engage it. Everything else, including all Ollama-served local models, stays unflagged and keeps normal tool exposure under `"auto"`. ### Models shipped by more than one provider Several vendors are reachable through more than one provider id: a subscription endpoint next to an API endpoint, or a gateway that resells another vendor's model. Because `"auto"` resolves the tier from whichever catalog served the run, two catalogs describing the same upstream model must not disagree by accident. Every catalog row for a shared model therefore states its tier explicitly once any sibling row states one. Rows are matched on the vendor's own name for the weights, so a catalog that republishes a model under a namespaced id or different casing is matched automatically: `novita/moonshotai/kimi-k3`, `nvidia/z-ai/glm-5.2`, and `together/deepseek-ai/DeepSeek-V4-Pro` all group with the first-party rows without anyone declaring anything. Only genuinely different names need the manifest's `upstreamModel` marker, as the `kimi` catalog uses for `moonshot/kimi-k3`. Reseller and aggregator catalogs such as `baseten`, `deepinfra`, `github-copilot`, `gmi`, `novita`, `nvidia`, `ollama-cloud`, `opencode`, `opencode-go`, `qianfan`, `together`, `venice`, and `volcengine-plan` currently declare `"capable"` for the models first-party catalogs flag `"preferred"`: the preferred tier came from evaluations on the first-party endpoints, and those runs have not been repeated per reseller. Promoting one of those rows is a deliberate, evidence-backed change rather than an oversight. For OpenAI models, the flag matters only when the run resolves to the OpenClaw embedded agent runtime. Default OpenAI routing uses the Codex-style harness surface, where OpenClaw code mode does not apply; the catalog flag never changes that routing decision. ### Choosing when to enable Code Mode can reduce token use by replacing repeated full tool schemas and intermediate model turns with a compact catalog and one program. Results depend on the model and workload. Compare correctness and full root-plus-descendant token use on representative tasks before forcing it broadly. Use `"auto"` when agents switch between models: preferred models get the compact surface, while other models keep normal tool exposure. Use `true` on an exact model entry when you have verified an unflagged model performs well with code mode. For open-weight or uncached serving where every prompt token is billed or recomputed, prefer enabling per model (via `"auto"` or an explicit model override) rather than globally, since the token savings depend on the model actually using the program surface well. ## Activation Code mode is evaluated after the effective tool policy is known and before the final model request is assembled: 1. Resolve the agent, model, provider, sandbox, channel, sender, and run policy. 2. Build the effective OpenClaw tool list, adding eligible plugin, MCP, and client tools. 3. Apply allow/deny policy. 4. Resolve activation using the [agent and model precedence](https://funcoding.ai/agents/openclaw/tools/code-mode/quickstart/#override-one-model). If it is `false`, or `"auto"` and the run's model is not catalog-preferred, continue with normal tool exposure. 5. If enabled and tools are active for the run, retain required direct-only tools and register every catalog-eligible effective tool in the code-mode catalog. 6. Remove the cataloged tools from the model-visible list; add `exec` and `wait` alongside the retained direct-only tools. Runs that intentionally have no tools (raw model calls, `disableTools: true`, or an empty `tools.allow` list) do not activate the code-mode surface even when `tools.codeMode.enabled: true` is configured. Code mode and OpenClaw Tool Search are mutually exclusive for a run; if code mode activates, Tool Search's compaction does not. The code-mode catalog is run-scoped and must not leak tools from another agent, session, sender, or run.