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Tools

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

  1. Enable the plugin:
json
{  "plugins": {    "entries": {      "llm-task": { "enabled": true }    }  }}
  1. Allow the tool:
json
{  "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)

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

allowedModels is an allowlist of provider/model strings; a request for any other model is rejected. All other keys are per-call fallbacks used when the tool call omits that parameter.

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.

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:

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

  • JSON-only: the model is instructed to return only a JSON value, no code fences, no commentary.
  • No tools: the underlying run has tools disabled, so the model cannot call out mid-task.
  • Treat output as untrusted unless you validate it with schema.
  • Put approvals before any side-effecting step (send, post, exec) that consumes this output.
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