jules-dispatch 🚀

Batch-dispatch tasks to Google Jules in parallel — and use it as an MCP tool inside Claude Code or OpenAI Codex CLI.

🌐 Languages: English · 简体中文

🌐 Landing page & interactive docs
https://yuuqq.github.io/jules-dispatch/ — full onboarding guide and MCP integration examples

What Is This?

jules-dispatch is a CLI and an MCP server for the Google Jules API that lets you:

Dispatch any number of Jules tasks with up to 50 concurrent session creations, optionally paced
Define tasks as simple YAML files — title, repo, branch, prompt
Poll for completion and collect generated PR links
Approve plans, send follow-up messages, cancel runaway sessions, tail live activity
Plug into Claude Code or Codex as an MCP server — your AI assistant calls Jules as a tool

It turns Jules from a "one task at a time" tool into a massively parallel coding workforce, controlled by either humans on the CLI or other AIs over MCP.

🏗 How It Works

flowchart LR
    O["🧠 Orchestrator<br/>(Claude / Codex / you)"]
    O -->|writes| T["📄 tasks/*.yaml"]
    T --> D["⚡ jules-dispatch batch"]
    D -->|parallel| J1["🤖 Jules #1"]
    D -->|parallel| J2["🤖 Jules #2"]
    D -->|parallel| J3["🤖 Jules #3"]
    D -->|parallel| J4["🤖 Jules #N"]
    J1 --> P1["🔀 PR #1"]
    J2 --> P2["🔀 PR #2"]
    J3 --> P3["🔀 PR #3"]
    J4 --> P4["🔀 PR #N"]

    classDef orch fill:#7c3aed,stroke:#5b21b6,color:#fff
    classDef tool fill:#0891b2,stroke:#0e7490,color:#fff
    classDef worker fill:#f59e0b,stroke:#b45309,color:#fff
    classDef pr fill:#10b981,stroke:#047857,color:#fff
    class O orch
    class D tool
    class J1,J2,J3,J4 worker
    class P1,P2,P3,P4 pr

✨ What's New in 1.2 — Optional AI Task Planning (BYO LLM)

Entirely optional. All core commands work without any LLM key. Skip this section if you only want raw dispatch.

Stop hand-writing task YAML. Give jules-dispatch one sentence and let an LLM expand it into N parallel Jules sessions.

$ jules-dispatch auto "Migrate every Express route to Fastify and add request-validation tests"

Planning with gpt-4o-mini...

Planned 6 task(s):
  1. Migrate auth routes (/api/auth/*) to Fastify
  2. Migrate user routes (/api/users/*) to Fastify
  3. Migrate billing routes (/api/billing/*) to Fastify
  4. Replace Express middleware with Fastify hooks
  5. Update server bootstrap to use Fastify instance
  6. Add Vitest request-validation tests for all migrated routes

Dispatch all 6 task(s)? [y/N]

Bring your own LLM — works with any OpenAI-compatible /chat/completions endpoint:

Provider	`LLM_BASE_URL`	Example `LLM_MODEL`
OpenAI (default)	(omit — defaults to `https://api.openai.com/v1`)	`gpt-4o-mini`, `gpt-4o`, `o3-mini`
OpenRouter	`https://openrouter.ai/api/v1`	`openrouter/auto`, `anthropic/claude-opus-4.7`
Ollama (local, free)	`http://localhost:11434/v1`	`llama3.1`, `qwen2.5-coder:32b`
Groq	`https://api.groq.com/openai/v1`	`llama-3.3-70b-versatile`
Together / Fireworks / DeepInfra / vLLM / LiteLLM / Azure OpenAI	(their endpoint)	(their model id)

Configure via env vars (LLM_API_KEY, LLM_BASE_URL, LLM_MODEL) or per-invocation flags (--llm-key, --llm-base-url, --llm-model). OPENAI_API_KEY and OPENROUTER_API_KEY are also recognised as fallbacks.

Command / Tool	What it does
`jules-dispatch plan-tasks "<intent>"`	Plan only — print or write tasks to a YAML file
`jules-dispatch auto "<intent>"`	Plan + dispatch in one shot (with confirmation)
MCP `jules_plan_tasks`	Same planning, exposed to Claude Code / Codex (only registered if an LLM key is configured)
MCP `jules_auto`	One-shot plan + dispatch (only registered if an LLM key is configured)

✨ What's New in 1.1

🧰 MCP server (jules-dispatch mcp) — 15 always-registered tools, plus 2 optional planning tools when an LLM key is configured
🤖 --json mode — machine-readable output on every command for AI agents and shell pipelines
✅ Plan approval workflow — plan, approve commands + requirePlanApproval: true task option
📡 Live tailing — tail <id> streams activity events as they happen
❌ Cancel sessions — cancel <id> aborts runaway runs
🔍 Direct lookup — get <id>, status --ids no longer limited to the recent page
🛡️ Real failure detection — uses session.state, fails fast, distinct exit codes
⚡ Smart retries — exponential backoff with jitter, honours Retry-After
📥 Stdin input — dispatch - reads YAML/JSON from a pipe
🔑 --api-key flag — pass keys per-invocation, no .env required

✨ Key Features

Feature	Details
⚡ Bounded, paced dispatch	Continuously replenish a 1–50 worker pool and optionally space launches with `--pace-ms`
📋 YAML task files	Multi-document YAML supported (`---` separators)
🔄 Status polling	Auto-detects PRs, plan approvals, failures
💬 Plan & message control	Approve plans, send follow-up messages, cancel sessions
🤖 MCP server	Drop into Claude Code or Codex as a tool
📦 Structured output	`--json` mode for clean piping into agents and scripts
📝 Dispatch logs	JSON audit trail of every dispatch run

💡 Five Common Use Cases

jules-dispatch works best when a change can be split into independent, PR-sized tasks. If tasks edit the same files or depend on earlier output, dispatch them in separate waves instead of running them concurrently.

1. Add test coverage across several modules

Suppose the auth, billing, users, and audit modules all need tests. Put one self-contained task file per module in a dedicated directory, then dispatch the directory as a batch:

jules-dispatch batch tasks/add-tests --parallel 4

Each Jules session owns one module. With AUTO_CREATE_PR enabled, the result is a set of focused PRs that can be reviewed and merged independently. A failed task can be retried without restarting the rest.

Why it helps: independent test work runs at the same time without turning into one large, hard-to-review change.

2. Break a large migration into executable tasks

For a goal such as migrating an Express API to Fastify, use the optional LLM planner to identify independent routes, middleware, startup code, and test work:

jules-dispatch auto "Migrate the Express API to Fastify and add request-validation tests" \
  --max 8 --parallel 4

auto shows the proposed tasks and asks for confirmation before dispatching them. Use plan-tasks instead when you want to save and edit the generated YAML before anything is sent to Jules.

Why it helps: the planner reduces the cost of decomposing a broad goal while keeping the task boundaries visible and reviewable.

3. Roll out the same change across multiple repositories

To add a shared CI check, security baseline, or contribution policy across several Jules-connected repositories, give each task its own source:

title: "Add the security baseline to the API"
prompt: "Add the agreed security checks and open a focused PR."
source: "sources/github/acme/api"
branch: "main"
---
title: "Add the security baseline to the worker"
prompt: "Add the agreed security checks and open a focused PR."
source: "sources/github/acme/worker"
branch: "main"

Place the task file in a dedicated batch directory and dispatch it with controlled concurrency and launch pacing:

jules-dispatch batch tasks/security-baseline --parallel 6 --pace-ms 250

Why it helps: one command coordinates the rollout while preserving a separate session and PR for each repository plus an audit log for the batch.

4. Keep a human approval gate for risky changes

Authentication, authorization, and database migrations often need review before implementation begins. Require Jules to stop after planning:

title: "Refactor authorization checks"
prompt: "Centralize API authorization checks without changing the public API."
requirePlanApproval: true

Inspect the plan, send corrections if needed, approve it, and then continue monitoring:

jules-dispatch plan abc123
jules-dispatch message abc123 "Do not change the public API"
jules-dispatch plan abc123       # inspect the revised plan
jules-dispatch approve abc123
jules-dispatch wait abc123

Why it helps: you keep control of high-impact decisions without giving up delegated execution.

5. Let Claude Code or Codex orchestrate the whole run

After configuring the MCP server, describe the outcome instead of operating each session yourself:

Analyze this repository, split its test gaps into independent tasks, and dispatch them to Jules. Ask me before approving plans or answering feedback requests. When every session finishes, summarize the outcome and PR URL for each task.

The coding assistant can call jules_dispatch, wait with jules_monitor, inspect action-required sessions with jules_interact, and return a final PR summary.

Why it helps: you manage the goal and the important decisions while the assistant handles dispatch, follow-up, and result collection.

🤖 Use Inside Claude Code or Codex (MCP)

The MCP server exposes Jules as a set of tools your coding AI can call directly.

sequenceDiagram
    autonumber
    actor U as 👤 You
    participant CC as 💬 Claude Code / Codex
    participant MCP as ⚡ jules-dispatch (MCP)
    participant J as ☁️ Google Jules

    U->>CC: "Add tests to 5 modules"
    CC->>MCP: jules_dispatch(tasks)
    MCP->>J: POST /sessions × 5
    J-->>MCP: 5 session IDs
    MCP-->>CC: {dispatched: 5}

    CC->>MCP: jules_monitor(ids, wait=true)
    loop until terminal or action required
        MCP->>J: GET /sessions/{id}
    end
    MCP-->>CC: {sessions, wait: {completed, actionRequired, ...}}

    opt a session requires action
        CC->>MCP: jules_interact(id)
        MCP-->>CC: state + plan + activities
        CC->>MCP: jules_approve_plan(id) or jules_send_message(id, text)
        CC->>MCP: jules_monitor(ids, wait=true)
    end

    CC->>MCP: jules_interact(id)
    MCP-->>CC: terminal status + PR output
    CC-->>U: "Done. PRs: #42, #43, #44, #45, #46"

Install for Claude Code

npm install -g @yuuqq/jules-dispatch

Full setup guide (including GSD integration): docs/MCP-INTEGRATION.md

Add to ~/.config/claude-code/mcp.json (or use claude mcp add):

{
  "mcpServers": {
    "jules-dispatch": {
      "command": "jules-dispatch",
      "args": ["--project", "/path/to/your/project", "mcp"],
      "env": {
        "JULES_API_KEY": "your-api-key-here",
        "JULES_DEFAULT_SOURCE": "sources/github/owner/repo",
        "JULES_DEFAULT_BRANCH": "main"
      }
    }
  }
}

Then in Claude Code: "Dispatch 5 Jules tasks to add tests to the auth, payments, users, sessions, and audit modules." Claude calls jules_dispatch, monitors them with jules_monitor, and uses jules_interact when it needs full context or PR output.

Install for OpenAI Codex CLI

Add to ~/.codex/config.toml:

[mcp_servers.jules-dispatch]
command = "jules-dispatch"
args = ["--project", "/path/to/your/project", "mcp"]
env = { JULES_API_KEY = "your-api-key-here", JULES_DEFAULT_SOURCE = "sources/github/owner/repo" }

Install as an Agent Skill

This repository also ships a lightweight skill wrapper at skills/jules-dispatch/. The skill teaches Claude Code, Codex, or any Agent Skills-compatible host when and how to use the jules-dispatch MCP tools.

For Codex, copy or install the folder as jules-dispatch in your Codex skills directory, then restart Codex:

cp -R skills/jules-dispatch "${CODEX_HOME:-$HOME/.codex}/skills/jules-dispatch"

For Agent Skills-compatible hosts that use a shared skills directory, copy the same folder into that host's skills directory. The skill is only the instruction layer; you still need the MCP server configured with jules-dispatch mcp and a valid JULES_API_KEY.

MCP Tools Exposed

Consolidated tools (recommended)

The server always registers 15 tools: 3 recommended consolidated tools, 5 utility tools, and 7 deprecated aliases. Two additional planning tools are registered when an LLM key is configured.

`jules_dispatch` — Create one or more sessions

Accepts a single task object, an array of tasks, or a YAML/JSON string.

Parameters:

Parameter	Type	Required	Default	Description
`tasks`	`object \| object[] \| string`	Yes	—	Task definition(s). Objects need `title` + `prompt`. Strings are parsed as YAML/JSON.
`format`	`"yaml" \| "json"`	No	`"yaml"`	Format when `tasks` is a string
`parallel`	`number`	No	`10`	Max concurrent dispatches (1–50)
`paceMs`	`number`	No	`0`	Global minimum delay between session creation starts (0–60000 ms)

{
  "tasks": [
    { "title": "Fix auth bug", "prompt": "Fix the null check in login()" },
    { "title": "Add tests", "prompt": "Add unit tests for auth.ts" }
  ],
  "parallel": 5,
  "paceMs": 250
}

Dispatch uses a continuously replenished worker pool rather than fixed waves: whenever one task finishes creating its session, the next queued task can start. paceMs applies globally across all workers, so consecutive creation starts are separated by at least that interval while result order still matches task order.

`jules_monitor` — Check status or wait for the next resolution point

Parameters:

Parameter	Type	Required	Default	Description
`sessionIds`	`string[]`	Yes	—	Session IDs to monitor
`wait`	`boolean`	No	`false`	If true, poll until all sessions are terminal, any session requires action, or the timeout expires
`intervalMs`	`number`	No	`10000`	Poll interval in ms (min 1000)
`timeoutMs`	`number`	No	`600000`	Max wait time in ms (min 1000)
`failFast`	`boolean`	No	`false`	Exit immediately on first failure

{
  "sessionIds": ["abc123", "def456"],
  "wait": true,
  "timeoutMs": 300000
}

Action-required states are AWAITING_PLAN_APPROVAL, AWAITING_USER_FEEDBACK, and PAUSED. When the result includes actionRequired, inspect those sessions with jules_interact, approve the plan or send feedback as appropriate, then call jules_monitor again for the unresolved IDs.

`jules_interact` — Inspect a session in full context

Returns session details, derived status, the globally latest plan, activity timeline, and PR output in one call. The server scans the complete oldest-first activity feed, then returns the newest activityCount entries in chronological order plus activityTotal for the full feed.

Parameters:

Parameter	Type	Required	Default	Description
`sessionId`	`string`	Yes	—	Session ID to inspect
`activityCount`	`number`	No	`10`	Number of recent activities (1–100)

{ "sessionId": "abc123", "activityCount": 20 }

Utility tools

Tool	Parameters	Description
`jules_list_sources`	(none)	List all GitHub repos connected to Jules
`jules_list_sessions`	`pageSize?`, `pageToken?`	List recent sessions with pagination
`jules_approve_plan`	`sessionId`	Approve a plan-gated session
`jules_send_message`	`sessionId`, `text`	Send a follow-up message
`jules_cancel_session`	`sessionId`	Cancel a running session

Optional LLM-powered tools (requires LLM key)

Tool	Parameters	Description
`jules_plan_tasks`	`description`, `maxTasks?`, `source?`, `branch?`, `context?`	Plan tasks from a high-level description
`jules_auto`	`description`, `maxTasks?`, `source?`, `branch?`, `parallel?`, `paceMs?`	Plan + dispatch in one shot

Response format

All tools return:

{ "success": true, "data": { ... } }

Errors return:

{
  "success": false,
  "error": {
    "message": "Authentication failed",
    "status": 401,
    "name": "Error",
    "recovery_hint": "Check your API key"
  }
}

Legacy tools (deprecated aliases)

jules_dispatch_task, jules_dispatch_batch, jules_get_session, jules_list_activities, jules_get_plan, jules_status, and jules_wait_for_completion remain functional for compatibility. New integrations should use the consolidated tools.

🚀 Quick Start (Plain CLI)

Prerequisites

Node.js 20+
A Google Jules account and API key
A GitHub repository connected to Jules

1. Install

npm install -g @yuuqq/jules-dispatch

2. Set up (interactive wizard)

jules-dispatch init

The wizard prompts for your API key, default source, and branch. It writes a .env file.

For CI/scripts (non-interactive):

jules-dispatch init --api-key sk-xxx --source sources/github/owner/repo

3. Validate your setup

jules-dispatch doctor

4. Write a task

# tasks/add-dark-mode.yaml
title: "Add Dark Mode Support"
prompt: |
  Add a dark mode toggle to the React app:
  1. Add a ThemeContext with light/dark state
  2. Wrap App with ThemeProvider
  3. Add a toggle button in the Header
  4. Persist preference in localStorage
  5. Open a PR

5. Dispatch it

jules-dispatch dispatch tasks/add-dark-mode.yaml
# ✓ Add Dark Mode Support
#   Session: https://jules.google.com/session/abc123
#   ID:      abc123

6. Batch-dispatch a whole directory

jules-dispatch batch tasks/ --parallel 10

That's it — 6 steps from install to your first PR.

📖 CLI Reference

Global flags

Flag	Default	Description
`-p, --project <dir>`	`.`	Directory containing your `.env` file
`--api-key <key>`		Jules API key (overrides `JULES_API_KEY`)
`--json`	off	Machine-readable output. NDJSON for streaming commands.

Commands

Command	What it does
`init`	Interactive first-run wizard (API key, source, branch)
`dispatch <taskFile>`	Dispatch a single task. Use `-` to read from stdin.
`batch [taskDir]`	Dispatch all `.yaml`/`.yml`/`.json` files in a directory
`auto <description>`	LLM-plan + dispatch in one shot (with confirmation)
`plan-tasks <description>`	Use LLM to expand an intent into N task drafts (no dispatch)
`status`	Summary of recent sessions (or specific `--ids`)
`get <sessionId>`	Full details of one session
`wait <ids...>`	Poll until sessions are terminal, require action, or time out
`tail <sessionId>`	Live-stream activity events for a session
`plan <sessionId>`	Show the most recent generated plan
`approve <sessionId>`	Approve a pending plan
`message <sessionId> <text>`	Send a follow-up message
`cancel <sessionId>`	Cancel a running session
`sources`	List connected GitHub repos (auto-paginates)
`doctor`	Validate environment, API key, connectivity, task files
`mcp`	Run as an MCP server over stdio

Exit codes (for shell scripts and agents)

Code	Meaning
`0`	Success
`1`	Generic error
`2`	Authentication error (missing or rejected API key)
`3`	Validation or configuration error (bad task file, args, or Jules settings)
`4`	Partial failure (some `batch` tasks failed)
`5`	Timeout (`wait` ran out of time)

Monitoring error behavior

status reports session or activity lookup failures explicitly as status: "error" and exits nonzero instead of fabricating a Jules failure or trusting a potentially stale state. Polling commands retry only network, rate-limit, and server errors; invalid requests, authentication failures, and missing sessions fail immediately with the affected session ID in the error context.

`dispatch` examples

# Override repo/branch
jules-dispatch dispatch tasks/my-task.yaml \
  --source sources/github/org/other-repo --branch develop

# Read from stdin
echo 'title: Quick fix\nprompt: Fix typo in README' | jules-dispatch dispatch -

# JSON output (great for piping)
jules-dispatch dispatch tasks/my-task.yaml --json | jq -r '.sessionId'

`batch` examples

jules-dispatch batch tasks/                       # default tasks/ dir
jules-dispatch batch tasks/ --parallel 20         # 20 concurrent
jules-dispatch batch tasks/ --parallel 10 --pace-ms 250  # globally space starts by 250 ms
jules-dispatch batch tasks/ --no-log              # don't write dispatch log
jules-dispatch batch tasks/ --json                # one JSON summary at the end

batch and auto both use the same continuously replenished worker pool. --parallel caps in-flight session creation and --pace-ms sets the global minimum spacing between creation starts; it does not add a delay separately inside each worker.

`wait` example

# Chain dispatch → wait via JSON output:
ID=$(jules-dispatch dispatch tasks/x.yaml --json | jq -r '.sessionId')
jules-dispatch wait "$ID" --interval 10000 --timeout 1800000

`tail` example

jules-dispatch tail abc123                        # human-readable stream
jules-dispatch tail abc123 --json                 # NDJSON event stream

🔄 Session Lifecycle

jules-dispatch tracks every Jules session through its full lifecycle and surfaces each state through the CLI / MCP:

stateDiagram-v2
    [*] --> QUEUED
    QUEUED --> PLANNING
    PLANNING --> IN_PROGRESS
    PLANNING --> AWAITING_PLAN_APPROVAL: approval required
    AWAITING_PLAN_APPROVAL --> IN_PROGRESS: approve plan
    IN_PROGRESS --> AWAITING_USER_FEEDBACK: input required
    AWAITING_USER_FEEDBACK --> IN_PROGRESS: send feedback
    IN_PROGRESS --> PAUSED: execution paused
    PAUSED --> IN_PROGRESS: execution resumes
    IN_PROGRESS --> COMPLETED: success
    IN_PROGRESS --> FAILED: error
    COMPLETED --> [*]
    FAILED --> [*]

Official state	Meaning	Recommended action
`STATE_UNSPECIFIED`	No specific state was supplied	Recheck with `jules_monitor` or inspect with `jules_interact`
`QUEUED` / `PLANNING` / `IN_PROGRESS`	Jules is actively progressing	Continue monitoring; use `tail` for live activity
`AWAITING_PLAN_APPROVAL`	The generated plan needs approval	Review with `jules_interact`, then use `approve` / `jules_approve_plan`
`AWAITING_USER_FEEDBACK`	Jules needs clarification or input	Inspect context, then use `message` / `jules_send_message`
`PAUSED`	Execution is paused and needs attention	Inspect context, provide guidance if appropriate, then monitor again
`COMPLETED`	Terminal success	Inspect the session and collect PR output
`FAILED`	Terminal failure	Inspect the newest failure activity and decide whether to retry or replace the task

For compatibility, jules-dispatch also normalizes legacy API states: PENDING, RUNNING, AWAITING_USER_INPUT, CANCELLED, and CANCELED. Cancellation is sent with the Jules DELETE /sessions/{id} operation.

📄 Task File Format

Field Reference

Field	Type	Required	Default	Description
`title`	`string`	Yes	—	Human-readable task name shown in CLI status and session lists
`prompt`	`string`	Yes	—	Detailed instructions for the Jules agent. The more specific, the better the output.
`source`	`string`	No	`JULES_DEFAULT_SOURCE` from `.env`	Jules source identifier, e.g. `sources/github/owner/repo`. Override per-task.
`branch`	`string`	No	`JULES_DEFAULT_BRANCH` from `.env` (or `main`)	Git branch for the Jules session to start from
`autoMode`	`string`	No	`AUTO_CREATE_PR`	Automation mode. Values: `AUTO_CREATE_PR` (Jules creates a PR automatically), `NONE`
`requirePlanApproval`	`boolean`	No	`false`	When `true`, Jules pauses after generating a plan and waits for `jules-dispatch approve <id>`

YAML example

title: "Add unit tests for auth module"
prompt: |
  Add comprehensive unit tests for src/auth.ts:
  1. Test login with valid credentials
  2. Test login with invalid credentials
  3. Test token refresh flow
  4. Test session expiry handling
  5. Open a PR with the test file
source: "sources/github/myorg/myrepo"
branch: "develop"
autoMode: "AUTO_CREATE_PR"
requirePlanApproval: false

Multiple tasks in one file (YAML `---` separators)

title: "Fix lint errors in src/auth"
prompt: "Fix all ESLint errors in src/auth.ts"
---
title: "Fix lint errors in src/api"
prompt: "Fix all ESLint errors in src/api.ts"
---
title: "Fix lint errors in src/utils"
prompt: "Fix all ESLint errors in src/utils.ts"

JSON format

{
  "title": "Fix the thing",
  "prompt": "Find the bug in src/auth.ts and fix it.",
  "source": "sources/github/owner/repo",
  "branch": "main"
}

JSON array (for batch dispatch via MCP):

[
  { "title": "Task 1", "prompt": "Do thing A" },
  { "title": "Task 2", "prompt": "Do thing B" }
]

🤖 AI-Orchestrated Parallel Development

The killer use case: combine jules-dispatch with Claude Code or Codex.

"I have a Node.js backend that needs to be migrated from Express to Fastify. Analyse the codebase, split the work into independent migration units, and dispatch them all to Jules in parallel using the jules-dispatch MCP tools. Then poll for completion and report back the PR URLs."

With the MCP server installed, your assistant will:

Analyse your codebase
Commit and push the target branch, because Jules works from the remote source branch rather than unpushed local changes
Call jules_dispatch with N task definitions
Call jules_monitor with wait: true; if action is required, inspect with jules_interact, approve or send feedback, and monitor again
Use jules_interact to collect terminal context and PR URLs

You get N parallel coding agents orchestrated by one strategic agent, hands-free.

📁 Project Structure

jules-dispatch/
├── src/
│   ├── cli.ts          CLI entry point (Commander)
│   ├── client.ts       Jules REST client (retries, pagination)
│   ├── config.ts       .env + task file loading
│   ├── dispatcher.ts   Task dispatch logic
│   ├── collector.ts    Status polling & wait
│   ├── errors.ts       Structured error translation (Problem/Cause/Fix)
│   ├── output.ts       Text vs JSON output mode, color detection
│   ├── init.ts         Interactive init wizard
│   ├── doctor.ts       Environment validation (doctor command)
│   ├── mcp.ts          MCP server (15 tools + 2 optional planner tools)
│   ├── mcp-helpers.ts  MCP response helpers (ok/fail/recovery hints)
│   ├── polling.ts      Shared poll-with-callback engine
│   ├── tail.ts         Bounded, cursor-aware activity tailing
│   ├── planner.ts      Optional LLM task planner
│   ├── log.ts          Verbose logging
│   └── types.ts        TypeScript types
├── tasks/              Your task YAMLs live here
├── .env                Generated by jules-dispatch init
└── .dispatch-logs/     JSON audit trail

🛠 Development

npm install
npm run build     # compile TypeScript → dist/
npm run dev       # run CLI directly with tsx
npm run lint
npm run test

📜 License

MIT — see LICENSE

Built to make Google Jules actually scale.

Name		Name	Last commit message	Last commit date
.dispatch-logs		.dispatch-logs
.github		.github
.planning		.planning
docs		docs
skills		skills
src		src
tasks		tasks
tests		tests
.env.example		.env.example
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
README.zh-CN.md		README.zh-CN.md
SECURITY.md		SECURITY.md
jules-ids.txt		jules-ids.txt
package-lock.json		package-lock.json
package.json		package.json
server.json		server.json
tsconfig.json		tsconfig.json
vitest.config.ts		vitest.config.ts

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jules-dispatch 🚀

What Is This?

🏗 How It Works

✨ What's New in 1.2 — Optional AI Task Planning (BYO LLM)

✨ What's New in 1.1

✨ Key Features

💡 Five Common Use Cases

1. Add test coverage across several modules

2. Break a large migration into executable tasks

3. Roll out the same change across multiple repositories

4. Keep a human approval gate for risky changes

5. Let Claude Code or Codex orchestrate the whole run

🤖 Use Inside Claude Code or Codex (MCP)

Install for Claude Code

Install for OpenAI Codex CLI

Install as an Agent Skill

MCP Tools Exposed

Consolidated tools (recommended)

jules_dispatch — Create one or more sessions

jules_monitor — Check status or wait for the next resolution point

jules_interact — Inspect a session in full context

Utility tools

Optional LLM-powered tools (requires LLM key)

Response format

Legacy tools (deprecated aliases)

🚀 Quick Start (Plain CLI)

Prerequisites

1. Install

2. Set up (interactive wizard)

3. Validate your setup

4. Write a task

5. Dispatch it

6. Batch-dispatch a whole directory

📖 CLI Reference

Global flags

Commands

Exit codes (for shell scripts and agents)

Monitoring error behavior

dispatch examples

batch examples

wait example

tail example

🔄 Session Lifecycle

📄 Task File Format

Field Reference

YAML example

Multiple tasks in one file (YAML --- separators)

JSON format

🤖 AI-Orchestrated Parallel Development

📁 Project Structure

🛠 Development

📜 License

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`jules_dispatch` — Create one or more sessions

`jules_monitor` — Check status or wait for the next resolution point

`jules_interact` — Inspect a session in full context

`dispatch` examples

`batch` examples

`wait` example

`tail` example

Multiple tasks in one file (YAML `---` separators)