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Edvisage Agent Connect

作者 Edvisage Global · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install edvisage-agent-connect
功能描述
Multi-agent coordination for AI agents — basic handoff protocols, shared context management, and team task delegation.
使用说明 (SKILL.md)

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.

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

Want role-based routing, automated context sync, capability matching, and more? → Upgrade to agent-connect-pro: https://edvisage.gumroad.com/l/[TBD]

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

安全使用建议
This skill is essentially a handbook of templates for multi-agent coordination — there is no code and it doesn't request any secrets, so it's internally coherent. Before installing or enabling agents to use it autonomously: 1) decide and lock down where shared context and logs will be stored (local sandboxed storage vs. networked endpoint) and who can read them; 2) ensure agents do not place secrets or PII into shared context files; 3) define who the 'owner' or escalation contact is so agents don't arbitrarily transmit data; 4) test the templates in a restricted environment to confirm agents follow your storage/communication policies; and 5) be cautious about enabling broad autonomous use if your agents can reach external networks — the skill's vague "confirm receipt" and "log" instructions could be implemented in many ways. If you want stronger guarantees (automatic encryption, access control, vetted endpoints), this skill in its current form does not provide them.
功能分析
Type: OpenClaw Skill Name: edvisage-agent-connect Version: 1.0.0 The skill bundle provides organizational protocols and templates for multi-agent coordination, including handoff and delegation frameworks. It contains no executable code, network requests, or instructions that deviate from its stated purpose of improving agent teamwork. All files (SKILL.md, package.json, README.md) are consistent with a benign utility.
能力评估
Purpose & Capability
Name, description, and included files (SKILL.md, README, package.json) consistently present multi-agent handoff, shared context, and delegation templates. There are no extra binaries, environment variables, or unrelated dependencies requested.
Instruction Scope
SKILL.md provides templates and behavioral norms (handoff format, shared context file structure, delegation checks, conflict resolution). These are high-level guidelines and do not include commands, file paths, network endpoints, or automated syncing. That makes the scope narrow but also ambiguous — the agent (or implementer) must decide where to store the shared context, how to confirm receipts, and where to log conflicts.
Install Mechanism
Instruction-only skill with no install spec and no code files to execute. Lowest-risk install profile: nothing is downloaded or written by a packaged installer.
Credentials
No environment variables, credentials, or config paths are requested. The guidance does not instruct access to unrelated secrets or system resources.
Persistence & Privilege
Skill is not always-enabled and does not request elevated or persistent platform privileges. It does not modify other skills or system-wide settings; it's purely a set of behavioral templates.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install edvisage-agent-connect
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /edvisage-agent-connect 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
agent-connect 1.0.0 — Initial Release - Introduces structured protocols for multi-agent handoff, including standardized task delegation and return processes. - Adds shared context management templates to enable teamwork, status tracking, and knowledge sharing across agents. - Provides a clear task delegation framework with best practices and risk assessment steps. - Establishes team communication norms for explicit, accountable, and minimal information exchange. - Includes a basic conflict resolution process for handling disagreements or conflicting outputs. - Lists key limitations of the free version (manual context sharing, no automated syncing, and basic delegation).
元数据
Slug edvisage-agent-connect
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Edvisage Agent Connect 是什么?

Multi-agent coordination for AI agents — basic handoff protocols, shared context management, and team task delegation. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 138 次。

如何安装 Edvisage Agent Connect?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install edvisage-agent-connect」即可一键安装,无需额外配置。

Edvisage Agent Connect 是免费的吗?

是的,Edvisage Agent Connect 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Edvisage Agent Connect 支持哪些平台?

Edvisage Agent Connect 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Edvisage Agent Connect?

由 Edvisage Global(@edvisage)开发并维护,当前版本 v1.0.0。

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