Lobster

An OpenClaw-native workflow shell: typed (JSON-first) pipelines, jobs, and approval gates.

Example of Lobster at work

OpenClaw (or any other AI agent) can use lobster as a workflow engine and avoid re-planning every step — saving tokens while improving determinism and resumability.

Watching a PR that hasn't had changes

node bin/lobster.js "workflows.run --name github.pr.monitor --args-json '{\"repo\":\"openclaw/openclaw\",\"pr\":1152}'"
[
  {
    "kind": "github.pr.monitor",
    "repo": "openclaw/openclaw",
    "prNumber": 1152,
    "key": "github.pr:openclaw/openclaw#1152",
    "changed": false,
    "summary": {
      "changedFields": [],
      "changes": {}
    },
    "prSnapshot": {
      "author": {
        "id": "MDQ6VXNlcjE0MzY4NTM=",
        "is_bot": false,
        "login": "vignesh07",
        "name": "Vignesh"
      },
      "baseRefName": "main",
      "headRefName": "feat/lobster-plugin",
      "isDraft": false,
      "mergeable": "MERGEABLE",
      "number": 1152,
      "reviewDecision": "",
      "state": "OPEN",
      "title": "feat: Add optional lobster plugin tool (typed workflows, approvals/resume)",
      "updatedAt": "2026-01-18T20:16:56Z",
      "url": "https://github.com/openclaw/openclaw/pull/1152"
    }
  }
]

And a PR that has a state change (in this case an approved PR)

 node bin/lobster.js "workflows.run --name github.pr.monitor --args-json '{\"repo\":\"openclaw/openclaw\",\"pr\":1200}'"
[
  {
    "kind": "github.pr.monitor",
    "repo": "openclaw/openclaw",
    "prNumber": 1200,
    "key": "github.pr:openclaw/openclaw#1200",
    "changed": true,
    "summary": {
      "changedFields": [
        "number",
        "title",
        "url",
        "state",
        "isDraft",
        "mergeable",
        "reviewDecision",
        "updatedAt",
        "baseRefName",
        "headRefName"
      ],
      "changes": {
        "number": {
          "from": null,
          "to": 1200
        },
        "title": {
          "from": null,
          "to": "feat(tui): add syntax highlighting for code blocks"
        },
        "url": {
          "from": null,
          "to": "https://github.com/openclaw/openclaw/pull/1200"
        },
        "state": {
          "from": null,
          "to": "MERGED"
        },
        "isDraft": {
          "from": null,
          "to": false
        },
        "mergeable": {
          "from": null,
          "to": "UNKNOWN"
        },
        "reviewDecision": {
          "from": null,
          "to": ""
        },
        "updatedAt": {
          "from": null,
          "to": "2026-01-19T05:06:09Z"
        },
        "baseRefName": {
          "from": null,
          "to": "main"
        },
        "headRefName": {
          "from": null,
          "to": "feat/tui-syntax-highlighting"
        }
      }
    },
    "prSnapshot": {
      "author": {
        "id": "MDQ6VXNlcjE0MzY4NTM=",
        "is_bot": false,
        "login": "vignesh07",
        "name": "Vignesh"
      },
      "baseRefName": "main",
      "headRefName": "feat/tui-syntax-highlighting",
      "isDraft": false,
      "mergeable": "UNKNOWN",
      "number": 1200,
      "reviewDecision": "",
      "state": "MERGED",
      "title": "feat(tui): add syntax highlighting for code blocks",
      "updatedAt": "2026-01-19T05:06:09Z",
      "url": "https://github.com/openclaw/openclaw/pull/1200"
    }
  }
]

Goals

• Typed pipelines (objects/arrays), not text pipes.
• Local-first execution.
• No new auth surface: Lobster must not own OAuth/tokens.
• Composable macros that OpenClaw (or any agent) can invoke in one step to save tokens.

Quick start

From this folder:

• pnpm install
• pnpm test
• pnpm lint
• node ./bin/lobster.js --help
• node ./bin/lobster.js doctor
• node ./bin/lobster.js "exec --json --shell 'echo [1,2,3]' | where '0>=0' | json"

Notes

• pnpm test runs tsc and then executes tests against dist/.
• bin/lobster.js prefers the compiled entrypoint in dist/ when present.

Commands

• exec: run OS commands
• exec --stdin raw|json|jsonl: feed pipeline input into subprocess stdin
• where, pick, head: data shaping
• json, table: renderers
• approve: approval gate (TTY prompt or --emit for OpenClaw integration)

Next steps

• OpenClaw integration: ship as an optional OpenClaw plugin tool.

Workflow files

Lobster workflow files are meant to read like small scripts:

• run: or command: for deterministic shell/CLI steps
• pipeline: for native Lobster stages like llm.invoke
• approval: for hard workflow gates between steps
• stdin: $step.stdout or stdin: $step.json to pass data forward

lobster run path/to/workflow.lobster
lobster run --file path/to/workflow.lobster --args-json '{"tag":"family"}'

Example file:

name: jacket-advice
args:
  location:
    default: Phoenix
steps:
  - id: fetch
    run: weather --json ${location}

  - id: confirm
    approval: Want jacket advice from the LLM?
    stdin: $fetch.json

  - id: advice
    pipeline: >
      llm.invoke --prompt "Given this weather data, should I wear a jacket?
      Be concise and return JSON."
    stdin: $fetch.json
    when: $confirm.approved

Notes:

• run: and command: are equivalent; run: is the preferred spelling for new files.
• pipeline: shares the same args/env/results model as shell steps, so later steps can still reference $step.stdout or $step.json.
• If you need a human checkpoint before an LLM call, use a dedicated approval: step in the workflow file rather than approve inside the nested pipeline.
• cwd, env, stdin, when, and condition work for both shell and pipeline steps.
• Use retry, timeout_ms, and on_error per step to control transient-failure behavior and recovery.
• Approval steps can optionally enforce identity constraints:
  • approval.required_approver (or requiredApprover) requires an exact approver id.
  • approval.require_different_approver (or requireDifferentApprover) requires approver id to differ from initiator.
  • approval.initiated_by (or initiatedBy) sets the initiator id for comparison.
  • LOBSTER_APPROVAL_INITIATED_BY can provide a default initiator id at run time.
  • LOBSTER_APPROVAL_APPROVED_BY is used at resume/approval time for identity checks.

Visualizing workflows

Use lobster graph to inspect workflow structure before execution.

lobster graph --file path/to/workflow.lobster
lobster graph --file path/to/workflow.lobster --format mermaid
lobster graph --file path/to/workflow.lobster --format dot
lobster graph --file path/to/workflow.lobster --format ascii
lobster graph --file path/to/workflow.lobster --args-json '{"location":"Seattle"}'

What gets visualized:

• each workflow step as a node (run, pipeline, approval, etc.)
• data-flow edges from stdin: $step.stdout / $step.json references
• conditional dependencies from when: / condition: expressions
• approval gates as diamond-shaped nodes in mermaid and dot output

Format notes:

• mermaid (default): emits flowchart TD text for GitHub/Markdown rendering
• dot: emits Graphviz DOT syntax
• ascii: emits a terminal-friendly node/edge list

Calling LLMs from workflows

Use llm.invoke from a native pipeline: step for model-backed work:

llm.invoke --prompt 'Summarize this diff'
llm.invoke --provider openclaw --prompt 'Summarize this diff'
llm.invoke --provider pi --prompt 'Summarize this diff'

Provider resolution order:

• --provider
• LOBSTER_LLM_PROVIDER
• auto-detect from environment

Built-in providers today:

• openclaw via OPENCLAW_URL / OPENCLAW_TOKEN
• pi via LOBSTER_PI_LLM_ADAPTER_URL (typically supplied by the Pi extension)
• http via LOBSTER_LLM_ADAPTER_URL

llm_task.invoke remains available as a backward-compatible alias for the OpenClaw provider.

pipeline: vs run: for LLM calls

• Use pipeline: for llm.invoke and llm_task.invoke (they are Lobster pipeline stages, not shell executables).
• Use run: only for real binaries in your shell (for example openclaw.invoke).

Example (stdin from a prior step is passed to the LLM as artifacts):

steps:
  - id: make_words
    run: echo "One two three four five six"

  - id: count_words
    pipeline: llm_task.invoke --prompt "How many words have been pasted below?"
    stdin: $make_words.stdout

Calling OpenClaw tools from workflows

Shell run: steps execute in your system shell, so OpenClaw tool calls there must be real executables.

If you install Lobster via npm/pnpm, it installs a small shim executable named:

• openclaw.invoke (preferred)
• clawd.invoke (alias)

These shims forward to the Lobster pipeline command of the same name.

Example: invoke llm-task

Prereqs:

• OPENCLAW_URL points at a running OpenClaw gateway
• optionally OPENCLAW_TOKEN if auth is enabled

export OPENCLAW_URL=http://127.0.0.1:18789
# export OPENCLAW_TOKEN=...

In a workflow:

name: hello-world
steps:
  - id: greeting
    run: >
      openclaw.invoke --tool llm-task --action json --args-json '{"prompt":"Hello"}'

Passing data between steps (no temp files)

Use stdin: $stepId.stdout to pipe output from one step into the next.

Args and shell-safety

${arg} substitution is a raw string replace into the shell command text.

For anything that may contain quotes, $, backticks, or newlines, prefer env vars:

• every resolved workflow arg is exposed as LOBSTER_ARG_<NAME> (uppercased, non-alnum → _)
• the full args object is also available as LOBSTER_ARGS_JSON

Example:

args:
  text:
    default: ""
steps:
  - id: safe
    env:
      TEXT: "$LOBSTER_ARG_TEXT"
    command: |
      jq -n --arg text "$TEXT" '{"result": $text}'