openclaw/docs/tools/lobster.md

summary, title, read_when

summary	title	read_when
Typed workflow runtime for OpenClaw with resumable approval gates.	Lobster	You want deterministic multi-step workflows with explicit approvals You need to resume a workflow without re-running earlier steps

Lobster runs multi-step tool pipelines as one deterministic tool call, with explicit approval checkpoints and resume tokens. It sits one layer above detached background work: for orchestrating flows across many detached tasks, see Task Flow (openclaw tasks flow); for the task activity ledger, see Background Tasks.

Why

Without Lobster, a multi-step job means many round-trip tool calls, with the model orchestrating every step. Lobster moves that orchestration into a typed runtime:

• One call instead of many: a single Lobster tool call returns a structured result for the whole pipeline.
• Approvals built in: side effects (send, post, delete) halt the workflow until explicitly approved.
• Resumable: a halted workflow returns a token; approve and resume without re-running earlier steps.

Lobster is a small, constrained DSL rather than a general scripting language: approve/resume is a durable, built-in primitive; pipelines are data (easy to log, diff, replay, review); the tiny grammar limits "creative" code paths so validation stays realistic; timeouts, output caps, sandbox checks, and allowlists are enforced by the runtime, not by each script. Each step can still call any CLI or script - generate .lobster files from other tooling if you want a richer authoring language.

Without Lobster, a recurring email triage looks like:

User: "Check my email and draft replies"
→ openclaw calls gmail.list
→ LLM summarizes
→ User: "draft replies to #2 and #5"
→ LLM drafts
→ User: "send #2"
→ openclaw calls gmail.send
(repeat daily, no memory of what was triaged)

With Lobster, the same job is one call that halts for approval and resumes:

{ "action": "run", "pipeline": "email.triage --limit 20", "timeoutMs": 30000 }

{
  "ok": true,
  "status": "needs_approval",
  "output": [{ "summary": "5 need replies, 2 need action" }],
  "requiresApproval": {
    "type": "approval_request",
    "prompt": "Send 2 draft replies?",
    "items": [],
    "resumeToken": "..."
  }
}

How it works

OpenClaw runs Lobster workflows in-process using the bundled @clawdbot/lobster package as an embedded runner. No external lobster subprocess is spawned; the tool call returns a JSON envelope directly. If the pipeline halts for approval, the envelope carries a resume token (or a short approval ID) so you can continue later.

Enable

Lobster is an optional plugin tool, not enabled by default. It ships bundled, so no separate install step is required - just allow the tool:

{
  "tools": {
    "alsoAllow": ["lobster"]
  }
}

Or per-agent:

{
  "agents": {
    "list": [
      {
        "id": "main",
        "tools": {
          "alsoAllow": ["lobster"]
        }
      }
    ]
  }
}

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

The tool is disabled entirely for sandboxed tool contexts.

If you need the standalone Lobster CLI for development or external pipelines (outside the embedded gateway runner), install it from the Lobster repo and put lobster on PATH.

Pattern: small CLI + JSON pipes + approvals

Build tiny commands that speak JSON, then chain them into one Lobster call. (Example command names below - swap in your own.)

inbox list --json
inbox categorize --json
inbox apply --json

{
  "action": "run",
  "pipeline": "exec --json --shell 'inbox list --json' | exec --stdin json --shell 'inbox categorize --json' | exec --stdin json --shell 'inbox apply --json' | approve --preview-from-stdin --limit 5 --prompt 'Apply changes?'",
  "timeoutMs": 30000
}

If the pipeline requests approval, resume with the token:

{
  "action": "resume",
  "token": "<resumeToken>",
  "approve": true
}

Example: map input items into tool calls:

gog.gmail.search --query 'newer_than:1d' \
  | openclaw.invoke --tool message --action send --each --item-key message --args-json '{"provider":"telegram","to":"..."}'

JSON-only LLM steps (llm-task)

For a structured LLM step inside a workflow, enable the optional llm-task plugin tool and call it from Lobster:

{
  "plugins": {
    "entries": {
      "llm-task": { "enabled": true }
    }
  },
  "agents": {
    "list": [
      {
        "id": "main",
        "tools": { "alsoAllow": ["llm-task"] }
      }
    ]
  }
}

Important limitation: embedded Lobster vs openclaw.invoke

The bundled Lobster plugin runs workflows in-process inside the gateway. In that embedded mode, openclaw.invoke does not automatically inherit a gateway URL/auth context for nested OpenClaw CLI tool calls.

That means this pattern is not currently reliable in the embedded runner:

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

Use the example below only when running the standalone Lobster CLI in an environment where openclaw.invoke is already configured with the correct gateway/auth context.

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
  }
}'

If you are using the embedded Lobster plugin today, prefer either:

• a direct llm-task tool call outside Lobster, or
• non-openclaw.invoke steps inside the Lobster pipeline until a supported embedded bridge is added.

See LLM Task for details and configuration options.

Workflow files (.lobster)

Lobster can run YAML/JSON workflow files with name, args, steps, env, condition, and approval fields. Set pipeline to the file path in the tool call.

name: inbox-triage
args:
  tag:
    default: "family"
steps:
  - id: collect
    command: inbox list --json
  - id: categorize
    command: inbox categorize --json
    stdin: $collect.stdout
  - id: approve
    command: inbox apply --approve
    stdin: $categorize.stdout
    approval: required
  - id: execute
    command: inbox apply --execute
    stdin: $categorize.stdout
    condition: $approve.approved

Notes:

• stdin: $step.stdout and stdin: $step.json pass a prior step's output.
• condition (or when) can gate steps on $step.approved.

Tool parameters

run

{
  "action": "run",
  "pipeline": "gog.gmail.search --query 'newer_than:1d' | email.triage",
  "cwd": "workspace",
  "timeoutMs": 30000,
  "maxStdoutBytes": 512000
}

Run a workflow file with args:

{
  "action": "run",
  "pipeline": "/path/to/inbox-triage.lobster",
  "argsJson": "{\"tag\":\"family\"}"
}

Field	Default	Notes
pipeline	required	Inline pipeline string, or a path ending in .lobster/.yaml/.yml/.json for a workflow file.
cwd	gateway cwd	Relative working directory; must resolve inside the gateway working directory (absolute paths are rejected).
timeoutMs	20000	Aborts the run if exceeded.
maxStdoutBytes	512000	Aborts the run if captured stdout or stderr exceeds this size.
argsJson	-	JSON string of args for a workflow file (ignored for inline pipelines).

resume

{
  "action": "resume",
  "token": "<resumeToken>",
  "approve": true
}

resume accepts either token (the full resume token from requiresApproval) or approvalId (the short id from the same object) - use whichever the halted run returned. approve is required.

Managed Task Flow mode

Passing flowControllerId and flowGoal on run (or flowId and flowExpectedRevision on resume) drives the call through the plugin runtime's managed Task Flow API instead of returning a bare envelope: OpenClaw creates or resumes a durable flow record, applies the Lobster envelope to it (waiting on approval, succeeded/failed on completion), and returns { ok, envelope, flow, mutation }. This mode requires a bound Task Flow runtime and is intended for plugin/controller code that needs durable flow state across gateway restarts, not typical ad hoc agent use.

Output envelope

Lobster returns a JSON envelope with one of three statuses:

• ok - finished successfully
• needs_approval - paused; requiresApproval carries a resumeToken and a short approvalId, either of which can resume the run
• cancelled - explicitly denied or cancelled

The tool surfaces the envelope in both content (pretty JSON) and details (raw object).

Approvals

If requiresApproval is present, inspect the prompt and decide:

• approve: true - resume and continue side effects
• approve: false - cancel and finalize the workflow

Use approve --preview-from-stdin --limit N to attach a JSON preview to approval requests without custom jq/heredoc glue. Resume state is stored as small JSON files under the Lobster state directory (~/.lobster/state by default, override with LOBSTER_STATE_DIR); the token itself only encodes a pointer to that state, not the full pipeline state.

OpenProse

OpenProse pairs well with Lobster: use /prose to orchestrate multi-agent prep, then run a Lobster pipeline for deterministic approvals. If a Prose program needs Lobster, allow the lobster tool for sub-agents via tools.subagents.tools. See OpenProse.

Safety

• Local in-process only - workflows execute inside the gateway process; no network calls from the plugin itself.
• No secrets - Lobster doesn't manage OAuth; it calls OpenClaw tools that do.
• Sandbox-aware - disabled when the tool context is sandboxed.
• Hardened - timeouts and output caps enforced by the embedded runner.

Troubleshooting

Error	Cause / fix
lobster runtime timed out	Pipeline exceeded timeoutMs. Increase it or split the pipeline.
lobster stdout exceeded maxStdoutBytes (or stderr)	Captured output exceeded the cap. Raise maxStdoutBytes or reduce output.
run --args-json must be valid JSON	argsJson (workflow-file runs) failed to parse. Fix the JSON string.
lobster runtime failed (or another runtime_error message)	The embedded runtime returned an error envelope. Check gateway logs for details.

Learn more

• Plugins
• Plugin tool authoring

Case study: community workflows

One public example: a "second brain" CLI + Lobster pipelines that manage three Markdown vaults (personal, partner, shared). The CLI emits JSON for stats, inbox listings, and stale scans; Lobster chains those commands into workflows like weekly-review, inbox-triage, memory-consolidation, and shared-task-sync, each with approval gates. AI handles judgment (categorization) when available and falls back to deterministic rules when not.

• Thread: https://x.com/plattenschieber/status/2014508656335770033
• Repo: https://github.com/bloomedai/brain-cli

Related

• Automation - all automation mechanisms
• Tools Overview - all available agent tools