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Slack-AI Maestro Bridge - Backlog

✅ Agent Routing via @AIM:agent-name (COMPLETED)

The bridge now supports routing to any agent in the AI Maestro mesh network using the @AIM:agent-name convention.

Usage

@AIM:backend-api check the server status
@AIM:graph-query find all API endpoints

Messages without @AIM: prefix route to the default agent (configurable via DEFAULT_AGENT env var).

Response Format

Responses are prefixed with the agent name:

🤖 [backend-api] Server is healthy, all endpoints responding.

Multi-Workspace Support

Problem

Currently the bridge connects to a single Slack workspace. Each workspace requires its own Bot Token (xoxb-...).

Options

Option A: Multiple Bridge Instances

  • Run separate bridge processes per workspace
  • Each with its own .env file (.env.workspace1, .env.workspace2, etc.)
  • Simple but requires managing multiple processes

Option B: Single Bridge, Multiple Tokens

  • Modify bridge to accept array of workspace configs
  • Single process handles all workspaces
  • More complex but cleaner operationally

Steps to Add a Workspace

  1. Go to api.slack.com/apps
  2. Settings → Manage Distribution → Enable distribution
  3. Install to Another Workspace
  4. Get new Bot Token (xoxb-...)
  5. Configure and run bridge for that workspace

Future Improvements

High Priority

  • Agent routing via @AIM:agent-name ✅
  • Multi-workspace support (see above)
  • PM2 or systemd service for persistent running
  • Better error handling for rate limits (429)
  • Retry logic with exponential backoff

Medium Priority

  • Message queue to prevent rate limiting
  • Slack thread context preservation across sessions
  • File/image attachment support
  • Slash commands (/lola help)

Low Priority

  • Web dashboard for bridge status
  • Message history/logging
  • Per-channel or per-user preferences
  • Scheduled messages

Known Issues

  • 429 rate limiting - need to investigate source and add throttling