Edvisage Agent Connect

SKILL.md

---
name: agent-connect
description: Multi-agent coordination. Role registry, task routing, workload balancing, trust-verified handoffs. Free version — core functionality included. Pro version ($19) — priority queues, team performance tracking, capability matching. Upgrade: edvisage.gumroad.com/l/luhje
version: 1.0.1
author: Edvisage Global
homepage: https://edvisageglobal.com/ai-tools
tags: [multi-agent, coordination, teamwork, handoff, delegation, collaboration]
---

# agent-connect — Multi-Agent Coordination

**By Edvisage Global — the agent safety company**

Turn your agents into a team, not a collection of solo bots. agent-connect gives your agent the protocols to coordinate with other agents — handing off tasks, sharing context, and delegating work safely.

## What This Skill Does

When installed, your agent gains structured coordination capability — knowing
how to work with other agents, delegate tasks, share context, and maintain
accountability across a multi-agent system. This is the free version and
includes core functionality. The **Pro version ($19)** adds role-based routing,
automated context sync, capability matching, trust-verified handoffs, workload
balancing, and team performance tracking — upgrade at
https://edvisage.gumroad.com/l/luhje

---

## Core Capabilities

### 1. Agent Handoff Protocol

When passing work to another agent, follow this structure:

```
## Task Handoff

### From: [your agent name]
### To: [receiving agent name/role]
### Timestamp: [ISO 8601]

### Task Description
[Clear, specific description of what needs to be done]

### Context Provided
[All relevant context the receiving agent needs]

### Expected Output
[What you need back — format, content, deadline]

### Constraints
- [Any limitations or rules]
- [Budget/cost limits if applicable]
- [Time constraints]

### Success Criteria
[How to know the task was completed correctly]

### Return Protocol
[How and where to deliver the result]
```

### 2. Shared Context Management

When working in a multi-agent system, maintain a shared context file:

```
## Shared Context — [Team/Project Name]
Last updated: [timestamp] by [agent name]

### Active Agents
| Agent | Role | Status | Current Task |
|-------|------|--------|--------------|

### Shared Knowledge
- [Key facts all agents should know]
- [Decisions that have been made]
- [Constraints that apply to everyone]

### Task Queue
| Task | Assigned To | Status | Deadline |
|------|------------|--------|----------|

### Communication Log
| Time | From | To | Message |
|------|------|-----|---------|
```

### 3. Task Delegation Framework

Before delegating, assess:

1. **Can I do this myself?** (Don't delegate what you can handle efficiently)
2. **Does the other agent have the right skills?** (Check their capabilities)
3. **Is the context transferable?** (Can I explain this clearly enough?)
4. **Is there a cost benefit?** (Cheaper model for simpler subtasks)
5. **What's the risk?** (What happens if the delegated task fails?)

Delegation format:
```
## Delegated Task
- Task: [description]
- Reason for delegation: [why another agent is better suited]
- Assigned to: [agent]
- Priority: [low / medium / high / critical]
- Deadline: [if applicable]
- Fallback: [what to do if the task fails]
```

### 4. Team Communication Norms

Rules for multi-agent communication:

- **Be explicit**: Never assume another agent knows your context
- **Be structured**: Use consistent formats for all handoffs
- **Be verified**: Confirm receipt of delegated tasks
- **Be accountable**: Report outcomes of delegated tasks back to the delegator
- **Be minimal**: Share only the context needed, not your entire memory

### 5. Basic Conflict Resolution

When agents disagree or produce conflicting outputs:

1. Identify the conflict explicitly
2. Check which agent has more relevant context
3. Check which output better matches the original objective
4. If unclear, escalate to the owner with both options
5. Log the conflict and resolution for future reference

## Limitations (Free Version)

- Basic handoff templates (no role-based routing)
- Manual context sharing (no automated sync)
- Simple delegation (no capability matching)
- No trust verification between agents
- No performance tracking across agent teams
- No workload balancing

## About Edvisage Global

We build practical safety and operations tools for AI agents. Our skills are designed for the OpenClaw ecosystem and install in minutes.

Website: https://edvisageglobal.com/ai-tools