Configuration
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
1. Specialized agent teams
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.
2. Multi-language support
Group: "International Support"
Agents:
- Agent_EN (responds in English)
- Agent_DE (responds in German)
- Agent_ES (responds in Spanish)
3. Quality assurance workflows
Group: "Customer Support"
Agents:
- SupportAgent (provides answer)
- QAAgent (reviews quality, only responds if issues found)
4. Task automation
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.
[email protected]) - DMs: E.164 phone number (e.g.
+15551234567)
{
"broadcast": {
"[email protected]": ["alfred", "baerbel", "assistant3"]
}
}
Result: When OpenClaw would reply in this chat, it will run all three agents.
Processing strategy
Control how agents process messages:
parallel (default)
All agents process simultaneously:
{
"broadcast": {
"strategy": "parallel",
"[email protected]": ["alfred", "baerbel"]
}
}
sequential
Agents process in order (one waits for previous to finish):
{
"broadcast": {
"strategy": "sequential",
"[email protected]": ["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",
"[email protected]": ["code-reviewer", "security-auditor", "docs-generator"],
"[email protected]": ["support-en", "support-de"],
"+15555550123": ["assistant", "logger"]
}
}
How it works
Message flow
Incoming message arrives
A WhatsApp group or DM message arrives.
Broadcast check
System checks if peer ID is in broadcast.
If in broadcast list
- All listed agents process the message.
- Each agent has its own session key and isolated context.
- Agents process in parallel (default) or sequentially.
If not in broadcast list
Normal routing applies (first matching binding).
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 [email protected] with agents ["alfred", "baerbel"]:
Alfred's context
Session: agent:alfred:whatsapp:group:[email protected]
History: [user message, alfred's previous responses]
Workspace: /Users/user/openclaw-alfred/
Tools: read, write, exec
Bärbel's context
Session: agent:baerbel:whatsapp:group:[email protected]
History: [user message, baerbel's previous responses]
Workspace: /Users/user/openclaw-baerbel/
Tools: read only
Best practices
1. Keep agents focused
Design each agent with a single, clear responsibility:
{
"broadcast": {
"DEV_GROUP": ["formatter", "linter", "tester"]
}
}
✅ Good: Each agent has one job. ❌ Bad: One generic "dev-helper" agent.
2. Use descriptive names
Make it clear what each agent does:
{
"agents": {
"security-scanner": { "name": "Security Scanner" },
"code-formatter": { "name": "Code Formatter" },
"test-generator": { "name": "Test Generator" }
}
}
3. Configure different tool access
Give agents only the tools they need:
{
"agents": {
"reviewer": {
"tools": { "allow": ["read", "exec"] }
},
"fixer": {
"tools": { "allow": ["read", "write", "edit", "exec"] }
}
}
}
reviewer is read-only. fixer can read and write.
4. Monitor performance
With many agents, consider:
- Using
"strategy": "parallel"(default) for speed - Limiting broadcast groups to 5-10 agents
- Using faster models for simpler agents
5. Handle failures gracefully
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
Agents not responding
Check:
- Agent IDs exist in
agents.list. - Peer ID format is correct (e.g.,
[email protected]). - Agents are not in deny lists.
Debug:
tail -f ~/.openclaw/logs/gateway.log | grep broadcast
Only one agent responding
Cause: Peer ID might be in bindings but not broadcast.
Fix: Add to broadcast config or remove from bindings.
Performance issues
If slow with many agents:
- Reduce number of agents per group.
- Use lighter models (sonnet instead of opus).
- Check sandbox startup time.
Examples
Example 1: Code review team
{
"broadcast": {
"strategy": "parallel",
"[email protected]": [
"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"
Example 2: Multi-language support
{
"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
strategy"parallel" | "sequential"How to process agents. parallel runs all agents simultaneously; sequential runs them in array order.
[peerId]string[]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)