Vendor OpenClaw source as Adolf fork baseline
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Adolf is a fork/vendored clone of github.com/openclaw/openclaw (v2026.6.11),
free to diverge. Tree copied sans upstream .git; upstream remote added for
future syncs. Node pinned to 24 (.nvmrc); engines already require >=22.19.
Preserves docs/ARCHITECTURE.md.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LeqyaxJF2nbRXJtae2kNB2
This commit is contained in:
2026-07-05 09:36:54 +00:00
parent 3216769225
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---
summary: "JSON-only LLM tasks for workflows (optional plugin tool)"
read_when:
- You want a JSON-only LLM step inside workflows
- You need schema-validated LLM output for automation
title: "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 }
}
}
}
```
2. 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-5.5",
"defaultAuthProfileId": "main",
"allowedModels": ["openai/gpt-5.5"],
"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.
## Related
- [Thinking levels](/tools/thinking)
- [Sub-agents](/tools/subagents)
- [Slash commands](/tools/slash-commands)