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LLM task

docs/tools/llm-task.md

2026.5.123.1 KB
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llm-task is an optional plugin tool that runs a JSON-only LLM task and returns structured output (optionally validated against JSON Schema).

This is ideal for workflow engines like Lobster: you can add a single LLM step without writing custom OpenClaw code for each workflow.

Enable the plugin

  1. Enable the plugin:
json
{
  "plugins": {
    "entries": {
      "llm-task": { "enabled": true }
    }
  }
}
  1. Allow the optional tool:
json
{
  "tools": {
    "alsoAllow": ["llm-task"]
  }
}

Use tools.allow only when you want restrictive allowlist mode.

Config (optional)

json
{
  "plugins": {
    "entries": {
      "llm-task": {
        "enabled": true,
        "config": {
          "defaultProvider": "openai-codex",
          "defaultModel": "gpt-5.5",
          "defaultAuthProfileId": "main",
          "allowedModels": ["openai/gpt-5.4"],
          "maxTokens": 800,
          "timeoutMs": 30000
        }
      }
    }
  }
}

allowedModels is an allowlist of provider/model strings. If set, any request outside the list is rejected.

Tool parameters

  • prompt (string, required)
  • input (any, optional)
  • schema (object, optional JSON Schema)
  • provider (string, optional)
  • model (string, optional)
  • thinking (string, optional)
  • authProfileId (string, optional)
  • temperature (number, optional)
  • maxTokens (number, optional)
  • timeoutMs (number, optional)

thinking accepts the standard OpenClaw reasoning presets, such as low or medium.

Output

Returns details.json containing the parsed JSON (and validates against schema when provided).

Example: Lobster workflow step

Important limitation

The example below assumes the standalone Lobster CLI is running in an environment 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:

lobster
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:

lobster
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

  • The tool is JSON-only and instructs the model to output only JSON (no code fences, no commentary).
  • No tools are exposed to the model for this run.
  • Treat output as untrusted unless you validate with schema.
  • Put approvals before any side-effecting step (send, post, exec).