openclaw-mission-control
Coordinate AI agent teams via a Kanban task board with local JSON storage. Enables multi-agent workflows with a Team Lead assigning work and Worker Agents executing tasks via heartbeat polling. Perfect for building AI agent command centers.
What this skill does
# Mission Control
Coordinate a team of AI agents using a Kanban-style task board with HTTP API.
## Overview
Mission Control lets you run multiple AI agents that collaborate on tasks:
- **Team Lead**: Creates and assigns tasks, reviews completed work
- **Worker Agents**: Poll for tasks via heartbeat, execute work, log progress
- **Kanban Board**: Visual task management at `http://localhost:8080`
- **HTTP API**: Agents interact via REST endpoints
- **Local Storage**: All data stored in JSON files โ no external database needed
## Quick Start
### 1. Install the Kanban Board
```bash
# Clone the Mission Control app
git clone https://github.com/0xindiebruh/openclaw-mission-control.git
cd mission-control
# Install dependencies
npm install
# Start the server
npm run dev
```
The board runs at `http://localhost:8080`.
### 2. Configure Your Agents
Edit `lib/config.ts` to define your agent team:
```typescript
export const AGENT_CONFIG = {
brand: {
name: "Mission Control",
subtitle: "AI Agent Command Center",
},
agents: [
{
id: "lead",
name: "Lead",
emoji: "๐ฏ",
role: "Team Lead",
focus: "Strategy, task assignment",
},
{
id: "writer",
name: "Writer",
emoji: "โ๏ธ",
role: "Content",
focus: "Blog posts, documentation",
},
{
id: "growth",
name: "Growth",
emoji: "๐",
role: "Marketing",
focus: "SEO, campaigns",
},
{
id: "dev",
name: "Dev",
emoji: "๐ป",
role: "Engineering",
focus: "Features, bugs, code",
},
{
id: "ux",
name: "UX",
emoji: "๐จ",
role: "Product",
focus: "Design, activation",
},
{
id: "data",
name: "Data",
emoji: "๐",
role: "Analytics",
focus: "Metrics, reporting",
},
] as const,
};
```
### 3. Seed the Database (First Run)
Initialize the agents in the database:
```bash
curl -X POST http://localhost:8080/api/seed
```
This creates agent records from your `lib/config.ts` configuration. Safe to run multiple times โ it only adds missing agents.
### 4. Configure OpenClaw Multi-Agent Mode
Add each agent to your `~/.openclaw/config.json`:
```json
{
"sessions": {
"list": [
{
"id": "main",
"default": true,
"name": "Lead",
"workspace": "~/.openclaw/workspace"
},
{
"id": "writer",
"name": "Writer",
"workspace": "~/.openclaw/workspace-writer",
"agentDir": "~/.openclaw/agents/writer/agent",
"heartbeat": {
"every": "15m"
}
},
{
"id": "growth",
"name": "Growth",
"workspace": "~/.openclaw/workspace-growth",
"agentDir": "~/.openclaw/agents/growth/agent",
"heartbeat": {
"every": "15m"
}
},
{
"id": "dev",
"name": "Dev",
"workspace": "~/.openclaw/workspace-dev",
"agentDir": "~/.openclaw/agents/dev/agent",
"heartbeat": {
"every": "15m"
}
}
]
}
}
```
**Key fields:**
- `id`: Unique agent identifier (must match an agent ID in `lib/config.ts`)
- `workspace`: Agent's working directory for files
- `agentDir`: Contains `SOUL.md`, `HEARTBEAT.md`, and agent personality
- `heartbeat.every`: Polling frequency (e.g., `5m`, `15m`, `1h`)
### 5. Set up Agent Heartbeats
Each worker agent needs a `HEARTBEAT.md` in their `agentDir`:
````markdown
# Agent Heartbeat
## Step 1: Check for Tasks
```bash
curl "http://localhost:8080/api/tasks/mine?agent=writer"
```
````
## Step 2: Pick up `todo` tasks
```bash
curl -X POST "http://localhost:8080/api/tasks/{TASK_ID}/pick" \
-H "Content-Type: application/json" \
-d '{"agent": "writer"}'
```
## Step 3: Log Progress
```bash
curl -X POST "http://localhost:8080/api/tasks/{TASK_ID}/log" \
-H "Content-Type: application/json" \
-d '{"agent": "writer", "action": "progress", "note": "Working on..."}'
```
## Step 4: Complete Tasks
```bash
curl -X POST "http://localhost:8080/api/tasks/{TASK_ID}/complete" \
-H "Content-Type: application/json" \
-d '{
"agent": "writer",
"note": "Completed! Summary...",
"deliverables": ["path/to/output.md"]
}'
```
## Step 5: Check for @Mentions
```bash
curl "http://localhost:8080/api/mentions?agent=writer"
```
Mark as read when done.
````
Create the agent directories:
```bash
mkdir -p ~/.openclaw/agents/{writer,growth,dev,ux,data}/agent
mkdir -p ~/.openclaw/workspace-{writer,growth,dev,ux,data}
````
---
## Task Lifecycle
```
backlog โ todo โ in_progress โ review โ done
โ โ โ โ
โ โ โ โโ Team Lead approves
โ โ โโ Agent completes (โ review)
โ โโ Agent picks up (โ in_progress)
โโ Team Lead prioritizes (โ todo)
```
---
## Team Lead Operations
### Creating a Task
```bash
curl -X POST http://localhost:8080/api/tasks \
-H "Content-Type: application/json" \
-d '{
"title": "Task title",
"description": "Detailed description",
"priority": "high",
"assignee": "writer",
"tags": ["tag1", "tag2"],
"createdBy": "lead"
}'
```
**Priority:** `urgent`, `high`, `medium`, `low`
### Moving to Todo
```bash
curl -X PATCH "http://localhost:8080/api/tasks/{id}" \
-H "Content-Type: application/json" \
-d '{"status": "todo"}'
```
### Approving Completed Work
```bash
curl -X PATCH "http://localhost:8080/api/tasks/{id}" \
-H "Content-Type: application/json" \
-d '{"status": "done"}'
```
### Adding Deliverable Path
```bash
curl -X PATCH "http://localhost:8080/api/tasks/{id}" \
-H "Content-Type: application/json" \
-d '{"deliverable": "path/to/file.md"}'
```
---
## Worker Agent Operations
### Picking Up Tasks
```bash
curl -X POST "http://localhost:8080/api/tasks/{id}/pick" \
-H "Content-Type: application/json" \
-d '{"agent": "{AGENT_ID}"}'
```
### Logging Progress
```bash
curl -X POST "http://localhost:8080/api/tasks/{id}/log" \
-H "Content-Type: application/json" \
-d '{
"agent": "{AGENT_ID}",
"action": "progress",
"note": "Updated the widget component"
}'
```
**Actions:** `picked`, `progress`, `blocked`, `completed`
### Completing a Task
```bash
curl -X POST "http://localhost:8080/api/tasks/{id}/complete" \
-H "Content-Type: application/json" \
-d '{
"agent": "{AGENT_ID}",
"note": "Completed! Summary of changes...",
"deliverables": ["docs/api.md", "src/feature.js"]
}'
```
Deliverables render as markdown in the task view.
---
## Comments & @Mentions
### Adding a Comment
```bash
curl -X POST "http://localhost:8080/api/tasks/{id}/comments" \
-H "Content-Type: application/json" \
-d '{
"author": "agent-id",
"content": "Hey @other-agent, need your input here"
}'
```
### Checking for @Mentions
```bash
curl "http://localhost:8080/api/mentions?agent={AGENT_ID}"
```
### Marking Mentions as Read
```bash
curl -X POST "http://localhost:8080/api/mentions/read" \
-H "Content-Type: application/json" \
-d '{"agent": "{AGENT_ID}", "all": true}'
```
---
## API Reference
### Tasks
| Endpoint | Method | Description |
| ---------------------------- | ------ | ------------------------ |
| `/api/tasks` | GET | List all tasks |
| `/api/tasks` | POST | Create new task |
| `/api/tasks/{id}` | GET | Get task detail |
| `/api/tasks/{id}` | PATCH | Update task fields |
| `/api/tasks/{id}` | DELETE | Delete task |
| `/api/tasks/mine?agent={id}` | GET | Agent's assigned tasks |
| `/api/tasks/{id}/pick` | POST | Agent picks up task |
| `/api/tasks/{id}/log` | POST | Log work action |
| `/api/tasks/{id}/complete` | POST | Complete task (โ review) |
| `/api/tasks/{id}/comments` | POST | Add comment |
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