339 lines
10 KiB
Markdown
339 lines
10 KiB
Markdown
---
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title: Lobster
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summary: "Typed workflow runtime for Clawdbot with resumable approval gates."
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description: Typed workflow runtime for Clawdbot — composable pipelines with approval gates.
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read_when:
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- You want deterministic multi-step workflows with explicit approvals
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- You need to resume a workflow without re-running earlier steps
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---
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# Lobster
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Lobster is a workflow shell that lets Clawdbot run multi-step tool sequences as a single, deterministic operation with explicit approval checkpoints.
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## Hook
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Your assistant can build the tools that manage itself. Ask for a workflow, and 30 minutes later you have a CLI plus pipelines that run as one call. Lobster is the missing piece: deterministic pipelines, explicit approvals, and resumable state.
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## Why
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Today, complex workflows require many back-and-forth tool calls. Each call costs tokens, and the LLM has to orchestrate every step. Lobster moves that orchestration into a typed runtime:
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- **One call instead of many**: Clawdbot runs one Lobster tool call and gets a structured result.
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- **Approvals built in**: Side effects (send email, post comment) halt the workflow until explicitly approved.
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- **Resumable**: Halted workflows return a token; approve and resume without re-running everything.
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## Why a DSL instead of plain programs?
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Lobster is intentionally small. The goal is not "a new language," it's a predictable, AI-friendly pipeline spec with first-class approvals and resume tokens.
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- **Approve/resume is built in**: A normal program can prompt a human, but it can’t *pause and resume* with a durable token without you inventing that runtime yourself.
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- **Determinism + auditability**: Pipelines are data, so they’re easy to log, diff, replay, and review.
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- **Constrained surface for AI**: A tiny grammar + JSON piping reduces “creative” code paths and makes validation realistic.
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- **Safety policy baked in**: Timeouts, output caps, sandbox checks, and allowlists are enforced by the runtime, not each script.
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- **Still programmable**: Each step can call any CLI or script. If you want JS/TS, generate `.lobster` files from code.
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## How it works
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Clawdbot launches the local `lobster` CLI in **tool mode** and parses a JSON envelope from stdout.
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If the pipeline pauses for approval, the tool returns a `resumeToken` so you can continue later.
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## Pattern: small CLI + JSON pipes + approvals
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Build tiny commands that speak JSON, then chain them into a single Lobster call. (Example command names below — swap in your own.)
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```bash
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inbox list --json
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inbox categorize --json
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inbox apply --json
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```
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```json
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{
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"action": "run",
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"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?'",
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"timeoutMs": 30000
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}
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```
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If the pipeline requests approval, resume with the token:
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```json
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{
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"action": "resume",
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"token": "<resumeToken>",
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"approve": true
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}
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```
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AI triggers the workflow; Lobster executes the steps. Approval gates keep side effects explicit and auditable.
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Example: map input items into tool calls:
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```bash
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gog.gmail.search --query 'newer_than:1d' \
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| clawd.invoke --tool message --action send --each --item-key message --args-json '{"provider":"telegram","to":"..."}'
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```
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## JSON-only LLM steps (llm-task)
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For workflows that need a **structured LLM step**, enable the optional
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`llm-task` plugin tool and call it from Lobster. This keeps the workflow
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deterministic while still letting you classify/summarize/draft with a model.
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Enable the tool:
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```json
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{
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"plugins": {
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"entries": {
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"llm-task": { "enabled": true }
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}
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},
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"agents": {
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"list": [
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{
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"id": "main",
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"tools": { "allow": ["llm-task"] }
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}
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]
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}
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}
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```
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Use it in a pipeline:
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```lobster
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clawd.invoke --tool llm-task --action json --args-json '{
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"prompt": "Given the input email, return intent and draft.",
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"input": { "subject": "Hello", "body": "Can you help?" },
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"schema": {
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"type": "object",
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"properties": {
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"intent": { "type": "string" },
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"draft": { "type": "string" }
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},
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"required": ["intent", "draft"],
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"additionalProperties": false
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}
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}'
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```
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See [LLM Task](/tools/llm-task) for details and configuration options.
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## Workflow files (.lobster)
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Lobster can run YAML/JSON workflow files with `name`, `args`, `steps`, `env`, `condition`, and `approval` fields. In Clawdbot tool calls, set `pipeline` to the file path.
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```yaml
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name: inbox-triage
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args:
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tag:
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default: "family"
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steps:
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- id: collect
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command: inbox list --json
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- id: categorize
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command: inbox categorize --json
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stdin: $collect.stdout
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- id: approve
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command: inbox apply --approve
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stdin: $categorize.stdout
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approval: required
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- id: execute
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command: inbox apply --execute
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stdin: $categorize.stdout
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condition: $approve.approved
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```
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Notes:
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- `stdin: $step.stdout` and `stdin: $step.json` pass a prior step’s output.
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- `condition` (or `when`) can gate steps on `$step.approved`.
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## Install Lobster
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Install the Lobster CLI on the **same host** that runs the Clawdbot Gateway (see the [Lobster repo](https://github.com/clawdbot/lobster)), and ensure `lobster` is on `PATH`.
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If you want to use a custom binary location, pass an **absolute** `lobsterPath` in the tool call.
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## Enable the tool
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Lobster is an **optional** plugin tool (not enabled by default).
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Recommended (additive, safe):
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```json
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{
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"tools": {
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"alsoAllow": ["lobster"]
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}
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}
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```
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Or per-agent:
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```json
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{
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"agents": {
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"list": [
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{
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"id": "main",
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"tools": {
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"alsoAllow": ["lobster"]
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}
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}
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]
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}
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}
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```
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Avoid using `tools.allow: ["lobster"]` unless you intend to run in restrictive allowlist mode.
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Note: allowlists are opt-in for optional plugins. If your allowlist only names
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plugin tools (like `lobster`), Clawdbot keeps core tools enabled. To restrict core
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tools, include the core tools or groups you want in the allowlist too.
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## Example: Email triage
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Without Lobster:
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```
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User: "Check my email and draft replies"
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→ clawd calls gmail.list
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→ LLM summarizes
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→ User: "draft replies to #2 and #5"
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→ LLM drafts
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→ User: "send #2"
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→ clawd calls gmail.send
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(repeat daily, no memory of what was triaged)
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```
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With Lobster:
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```json
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{
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"action": "run",
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"pipeline": "email.triage --limit 20",
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"timeoutMs": 30000
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}
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```
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Returns a JSON envelope (truncated):
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```json
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{
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"ok": true,
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"status": "needs_approval",
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"output": [{ "summary": "5 need replies, 2 need action" }],
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"requiresApproval": {
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"type": "approval_request",
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"prompt": "Send 2 draft replies?",
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"items": [],
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"resumeToken": "..."
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}
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}
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```
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User approves → resume:
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```json
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{
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"action": "resume",
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"token": "<resumeToken>",
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"approve": true
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}
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```
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One workflow. Deterministic. Safe.
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## Tool parameters
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### `run`
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Run a pipeline in tool mode.
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```json
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{
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"action": "run",
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"pipeline": "gog.gmail.search --query 'newer_than:1d' | email.triage",
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"cwd": "/path/to/workspace",
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"timeoutMs": 30000,
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"maxStdoutBytes": 512000
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}
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```
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Run a workflow file with args:
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```json
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{
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"action": "run",
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"pipeline": "/path/to/inbox-triage.lobster",
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"argsJson": "{\"tag\":\"family\"}"
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}
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```
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### `resume`
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Continue a halted workflow after approval.
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```json
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{
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"action": "resume",
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"token": "<resumeToken>",
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"approve": true
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}
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```
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### Optional inputs
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- `lobsterPath`: Absolute path to the Lobster binary (omit to use `PATH`).
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- `cwd`: Working directory for the pipeline (defaults to the current process working directory).
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- `timeoutMs`: Kill the subprocess if it exceeds this duration (default: 20000).
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- `maxStdoutBytes`: Kill the subprocess if stdout exceeds this size (default: 512000).
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- `argsJson`: JSON string passed to `lobster run --args-json` (workflow files only).
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## Output envelope
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Lobster returns a JSON envelope with one of three statuses:
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- `ok` → finished successfully
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- `needs_approval` → paused; `requiresApproval.resumeToken` is required to resume
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- `cancelled` → explicitly denied or cancelled
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The tool surfaces the envelope in both `content` (pretty JSON) and `details` (raw object).
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## Approvals
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If `requiresApproval` is present, inspect the prompt and decide:
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- `approve: true` → resume and continue side effects
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- `approve: false` → cancel and finalize the workflow
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Use `approve --preview-from-stdin --limit N` to attach a JSON preview to approval requests without custom jq/heredoc glue. Resume tokens are now compact: Lobster stores workflow resume state under its state dir and hands back a small token key.
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## OpenProse
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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](/prose).
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## Safety
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- **Local subprocess only** — no network calls from the plugin itself.
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- **No secrets** — Lobster doesn't manage OAuth; it calls clawd tools that do.
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- **Sandbox-aware** — disabled when the tool context is sandboxed.
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- **Hardened** — `lobsterPath` must be absolute if specified; timeouts and output caps enforced.
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## Troubleshooting
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- **`lobster subprocess timed out`** → increase `timeoutMs`, or split a long pipeline.
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- **`lobster output exceeded maxStdoutBytes`** → raise `maxStdoutBytes` or reduce output size.
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- **`lobster returned invalid JSON`** → ensure the pipeline runs in tool mode and prints only JSON.
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- **`lobster failed (code …)`** → run the same pipeline in a terminal to inspect stderr.
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## Learn more
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- [Plugins](/plugin)
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- [Plugin tool authoring](/plugins/agent-tools)
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## Case study: community workflows
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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.
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- Thread: https://x.com/plattenschieber/status/2014508656335770033
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- Repo: https://github.com/bloomedai/brain-cli
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