12 KiB
summary, read_when, status, title, sidebarTitle
| summary | read_when | status | title | sidebarTitle | ||
|---|---|---|---|---|---|---|
| Broadcast a WhatsApp message to multiple agents |
|
experimental | Broadcast groups | Broadcast groups |
Overview
Broadcast Groups enable multiple agents to process and respond to the same message simultaneously. This allows you to create specialized agent teams that work together in a single WhatsApp group or DM — all using one phone number.
Current scope: WhatsApp only (web channel).
Broadcast groups are evaluated after channel allowlists and group activation rules. In WhatsApp groups, this means broadcasts happen when OpenClaw would normally reply (for example: on mention, depending on your group settings).
Use cases
Deploy multiple agents with atomic, focused responsibilities:```
Group: "Development Team"
Agents:
- CodeReviewer (reviews code snippets)
- DocumentationBot (generates docs)
- SecurityAuditor (checks for vulnerabilities)
- TestGenerator (suggests test cases)
```
Each agent processes the same message and provides its specialized perspective.
```
Group: "International Support"
Agents:
- Agent_EN (responds in English)
- Agent_DE (responds in German)
- Agent_ES (responds in Spanish)
```
```
Group: "Customer Support"
Agents:
- SupportAgent (provides answer)
- QAAgent (reviews quality, only responds if issues found)
```
```
Group: "Project Management"
Agents:
- TaskTracker (updates task database)
- TimeLogger (logs time spent)
- ReportGenerator (creates summaries)
```
Configuration
Basic setup
Add a top-level broadcast section (next to bindings). Keys are WhatsApp peer ids:
- group chats: group JID (e.g.
120363403215116621@g.us) - DMs: E.164 phone number (e.g.
+15551234567)
{
"broadcast": {
"120363403215116621@g.us": ["alfred", "baerbel", "assistant3"]
}
}
Result: When OpenClaw would reply in this chat, it will run all three agents.
Processing strategy
Control how agents process messages:
All agents process simultaneously:```json
{
"broadcast": {
"strategy": "parallel",
"120363403215116621@g.us": ["alfred", "baerbel"]
}
}
```
Agents process in order (one waits for previous to finish):
```json
{
"broadcast": {
"strategy": "sequential",
"120363403215116621@g.us": ["alfred", "baerbel"]
}
}
```
Complete example
{
"agents": {
"list": [
{
"id": "code-reviewer",
"name": "Code Reviewer",
"workspace": "/path/to/code-reviewer",
"sandbox": { "mode": "all" }
},
{
"id": "security-auditor",
"name": "Security Auditor",
"workspace": "/path/to/security-auditor",
"sandbox": { "mode": "all" }
},
{
"id": "docs-generator",
"name": "Documentation Generator",
"workspace": "/path/to/docs-generator",
"sandbox": { "mode": "all" }
}
]
},
"broadcast": {
"strategy": "parallel",
"120363403215116621@g.us": ["code-reviewer", "security-auditor", "docs-generator"],
"120363424282127706@g.us": ["support-en", "support-de"],
"+15555550123": ["assistant", "logger"]
}
}
How it works
Message flow
A WhatsApp group or DM message arrives. System checks if peer ID is in `broadcast`. - All listed agents process the message. - Each agent has its own session key and isolated context. - Agents process in parallel (default) or sequentially. Normal routing applies (first matching binding). Broadcast groups do not bypass channel allowlists or group activation rules (mentions/commands/etc). They only change _which agents run_ when a message is eligible for processing.Session isolation
Each agent in a broadcast group maintains completely separate:
- Session keys (
agent:alfred:whatsapp:group:120363...vsagent:baerbel:whatsapp:group:120363...) - Conversation history (agent doesn't see other agents' messages)
- Workspace (separate sandboxes if configured)
- Tool access (different allow/deny lists)
- Memory/context (separate IDENTITY.md, SOUL.md, etc.)
- Group context buffer (recent group messages used for context) is shared per peer, so all broadcast agents see the same context when triggered
This allows each agent to have:
- Different personalities
- Different tool access (e.g., read-only vs. read-write)
- Different models (e.g., opus vs. sonnet)
- Different skills installed
Example: isolated sessions
In group 120363403215116621@g.us with agents ["alfred", "baerbel"]:
Best practices
Design each agent with a single, clear responsibility:```json
{
"broadcast": {
"DEV_GROUP": ["formatter", "linter", "tester"]
}
}
```
✅ **Good:** Each agent has one job. ❌ **Bad:** One generic "dev-helper" agent.
Make it clear what each agent does:
```json
{
"agents": {
"security-scanner": { "name": "Security Scanner" },
"code-formatter": { "name": "Code Formatter" },
"test-generator": { "name": "Test Generator" }
}
}
```
Give agents only the tools they need:
```json
{
"agents": {
"reviewer": {
"tools": { "allow": ["read", "exec"] } // Read-only
},
"fixer": {
"tools": { "allow": ["read", "write", "edit", "exec"] } // Read-write
}
}
}
```
With many agents, consider:
- Using `"strategy": "parallel"` (default) for speed
- Limiting broadcast groups to 5-10 agents
- Using faster models for simpler agents
Agents fail independently. One agent's error doesn't block others:
```
Message → [Agent A ✓, Agent B ✗ error, Agent C ✓]
Result: Agent A and C respond, Agent B logs error
```
Compatibility
Providers
Broadcast groups currently work with:
- ✅ WhatsApp (implemented)
- 🚧 Telegram (planned)
- 🚧 Discord (planned)
- 🚧 Slack (planned)
Routing
Broadcast groups work alongside existing routing:
{
"bindings": [
{
"match": { "channel": "whatsapp", "peer": { "kind": "group", "id": "GROUP_A" } },
"agentId": "alfred"
}
],
"broadcast": {
"GROUP_B": ["agent1", "agent2"]
}
}
GROUP_A: Only alfred responds (normal routing).GROUP_B: agent1 AND agent2 respond (broadcast).
Troubleshooting
**Check:**1. Agent IDs exist in `agents.list`.
2. Peer ID format is correct (e.g., `120363403215116621@g.us`).
3. Agents are not in deny lists.
**Debug:**
```bash
tail -f ~/.openclaw/logs/gateway.log | grep broadcast
```
**Cause:** Peer ID might be in `bindings` but not `broadcast`.
**Fix:** Add to broadcast config or remove from bindings.
If slow with many agents:
- Reduce number of agents per group.
- Use lighter models (sonnet instead of opus).
- Check sandbox startup time.
Examples
```json { "broadcast": { "strategy": "parallel", "120363403215116621@g.us": [ "code-formatter", "security-scanner", "test-coverage", "docs-checker" ] }, "agents": { "list": [ { "id": "code-formatter", "workspace": "~/agents/formatter", "tools": { "allow": ["read", "write"] } }, { "id": "security-scanner", "workspace": "~/agents/security", "tools": { "allow": ["read", "exec"] } }, { "id": "test-coverage", "workspace": "~/agents/testing", "tools": { "allow": ["read", "exec"] } }, { "id": "docs-checker", "workspace": "~/agents/docs", "tools": { "allow": ["read"] } } ] } } ```**User sends:** Code snippet.
**Responses:**
- code-formatter: "Fixed indentation and added type hints"
- security-scanner: "⚠️ SQL injection vulnerability in line 12"
- test-coverage: "Coverage is 45%, missing tests for error cases"
- docs-checker: "Missing docstring for function `process_data`"
```json
{
"broadcast": {
"strategy": "sequential",
"+15555550123": ["detect-language", "translator-en", "translator-de"]
},
"agents": {
"list": [
{ "id": "detect-language", "workspace": "~/agents/lang-detect" },
{ "id": "translator-en", "workspace": "~/agents/translate-en" },
{ "id": "translator-de", "workspace": "~/agents/translate-de" }
]
}
}
```
API reference
Config schema
interface OpenClawConfig {
broadcast?: {
strategy?: "parallel" | "sequential";
[peerId: string]: string[];
};
}
Fields
How to process agents. `parallel` runs all agents simultaneously; `sequential` runs them in array order. WhatsApp group JID, E.164 number, or other peer ID. Value is the array of agent IDs that should process messages.Limitations
- Max agents: No hard limit, but 10+ agents may be slow.
- Shared context: Agents don't see each other's responses (by design).
- Message ordering: Parallel responses may arrive in any order.
- Rate limits: All agents count toward WhatsApp rate limits.
Future enhancements
Planned features:
- Shared context mode (agents see each other's responses)
- Agent coordination (agents can signal each other)
- Dynamic agent selection (choose agents based on message content)
- Agent priorities (some agents respond before others)