Broadcast Groups
Status: ExperimentalVersion: Added in 2026.1.9
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 provider). Broadcast groups are evaluated after provider allowlists and group activation rules. In WhatsApp groups, this means broadcasts happen when Clawdbot 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:2. Multi-Language Support
3. Quality Assurance Workflows
4. Task Automation
Configuration
Basic Setup
Add a top-levelbroadcast 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)
Processing Strategy
Control how agents process messages:Parallel (Default)
All agents process simultaneously:Sequential
Agents process in order (one waits for previous to finish):Complete Example
How It Works
Message Flow
- Incoming message arrives in a WhatsApp group
- 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
- 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:
Best Practices
1. Keep Agents Focused
Design each agent with a single, clear responsibility:❌ Bad: One generic “dev-helper” agent
2. Use Descriptive Names
Make it clear what each agent does:3. Configure Different Tool Access
Give agents only the tools they need: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:Compatibility
Providers
Broadcast groups currently work with:- ✅ WhatsApp (implemented)
- 🚧 Telegram (planned)
- 🚧 Discord (planned)
- 🚧 Slack (planned)
Routing
Broadcast groups work alongside existing routing:GROUP_A: Only alfred responds (normal routing)GROUP_B: agent1 AND agent2 respond (broadcast)
broadcast takes priority over bindings.
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
Only One Agent Responding
Cause: Peer ID might be inbindings 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
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
API Reference
Config Schema
Fields
strategy(optional): How to process agents"parallel"(default): All agents process simultaneously"sequential": Agents process in array order
[peerId]: WhatsApp group JID, E.164 number, or other peer ID- Value: 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)