LLM task

llm-task is a bundled optional plugin tool that runs a single JSON-only LLM call and returns structured output, optionally validated against a JSON Schema. It gives workflow engines like Lobster an LLM step without custom OpenClaw code per workflow.

Enable

Enable the plugin:

{
  "plugins": {
    "entries": {
      "llm-task": { "enabled": true }
    }
  }
}

Allow the tool:

{
  "tools": {
    "alsoAllow": ["llm-task"]
  }
}

alsoAllow adds llm-task on top of the active tool profile without restricting other core tools. Use tools.allow only if you want a restrictive allowlist mode instead.

Config (optional)

{
  "plugins": {
    "entries": {
      "llm-task": {
        "enabled": true,
        "llm": {
          "allowModelOverride": true,
          "allowedCompletionModels": ["openai/gpt-5.6-sol"],
          "allowAuthProfileOverride": true
        },
        "config": {
          "defaultProvider": "openai",
          "defaultModel": "gpt-5.6-sol",
          "defaultAuthProfileId": "main",
          "maxTokens": 800,
          "timeoutMs": 30000
        }
      }
    }
  }
}

The llm block is host-owned authorization. allowedCompletionModels restricts every completion, so include the resolved agent default as well as any override targets. allowAuthProfileOverride permits defaultAuthProfileId and the per-call authProfileId parameter. The config keys are selection defaults used when a tool call omits the corresponding parameter. Run openclaw doctor --fix once for llm-task entries created by older releases. Doctor grants the shipped model/profile selection permissions and moves any legacy config.allowedModels value into llm.allowedCompletionModels without widening it.

Tool parameters

Parameter	Type	Notes
`prompt`	string	Required. Task instruction for the LLM.
`input`	any	Optional payload; serialized to JSON and appended to the prompt.
`schema`	object	Optional JSON Schema the parsed output must validate against.
`provider`	string	Overrides `defaultProvider` / the agent’s default provider.
`model`	string	Overrides `defaultModel`; accepts bare model ids, aliases, or a `provider/model` ref (a duplicate provider prefix is stripped automatically).
`thinking`	string	Reasoning level (e.g. `low`, `medium`); must be one supported by the resolved model.
`authProfileId`	string	Overrides `defaultAuthProfileId`.
`temperature`	number	Best-effort; not all providers honor it.
`maxTokens`	number	Best-effort cap on output tokens.
`timeoutMs`	number	Run timeout; default `30000`.

Output

Returns details.json (the parsed, schema-validated JSON) plus details.provider and details.model naming what actually ran. Each call starts a fresh prompt-only inference operation. It does not reuse the calling agent’s transcript or native runtime session, run agent lifecycle hooks, or deliver model output to a channel. OpenClaw uses the selected provider, model, auth profile, and runtime exactly once; it does not fall back to another route when that owner cannot provide a literal zero-tool call. A selected agent harness must implement isolated completion. Otherwise the call fails before inference with a does not support isolated completion error. This fail-closed behavior prevents a JSON task from silently becoming a normal tool-capable agent turn. CLI runtimes must provide the equivalent isolated preparation guarantee. The bundled Claude and Gemini CLI runtimes do; a different CLI runtime that has not adopted this internal contract fails before its process starts. Gemini CLI isolated completion supports Gemini API-key and Vertex auth. Google OAuth and compute/Code Assist auth are rejected because managed-account policy can add administrator-required tools after local CLI settings are loaded. Gemini prompts containing native @path includes or a leading /command also fail before inference because Gemini CLI has no literal raw-input mode.

Example: Lobster workflow step

Important limitation

The example below assumes the standalone Lobster CLI is running where openclaw.invoke already has the correct gateway URL/auth context. For the bundled embedded Lobster runner inside OpenClaw, this nested CLI pattern is not currently reliable:

openclaw.invoke --tool llm-task --action json --args-json '{ ... }'

Until embedded Lobster has a supported bridge for this flow, prefer either:

direct llm-task tool calls outside Lobster, or
Lobster steps that do not rely on nested openclaw.invoke calls.

Standalone Lobster CLI example:

openclaw.invoke --tool llm-task --action json --args-json '{
  "prompt": "Given the input email, return intent and draft.",
  "thinking": "low",
  "input": {
    "subject": "Hello",
    "body": "Can you help?"
  },
  "schema": {
    "type": "object",
    "properties": {
      "intent": { "type": "string" },
      "draft": { "type": "string" }
    },
    "required": ["intent", "draft"],
    "additionalProperties": false
  }
}'

Safety notes

JSON-only: the model is instructed to return only a JSON value, no code fences, no commentary.
No tools: the selected runtime must expose a literal empty model-callable tool surface. OpenClaw rejects tool-shaped results instead of treating them as task output.
Isolated: the run has no agent transcript, session reuse, lifecycle hooks, channel delivery, or provider fallback.
Treat output as untrusted unless you validate it with schema.
Put approvals before any side-effecting step (send, post, exec) that consumes this output.

Overview

Plugins

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Skills

Automation

Tools

Agent coordination

Enable

Config (optional)

Tool parameters

Output

Example: Lobster workflow step

Important limitation

Safety notes

​Enable

​Config (optional)

​Tool parameters

​Output

​Example: Lobster workflow step

​Important limitation

​Safety notes

​Related

Enable

Config (optional)

Tool parameters

Output

Example: Lobster workflow step

Important limitation

Safety notes

Related