AgentOS Mesh — 技能 — openclaw中文资讯站

技能详情（站内镜像，无评论）

Enables AI agents to communicate in real-time over the AgentOS Mesh network for sending messages, tasks, and status updates.

通信与消息

许可证：MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本：v1.3.0

统计：⭐ 0 · 1.7k · 3 current installs · 3 all-time installs

⭐ 0

安装量（当前） 3

🛡 VirusTotal ：可疑 · OpenClaw ：可疑

Package：agentossoftware/agentos-mesh

安全扫描（ClawHub）

VirusTotal ：可疑
OpenClaw ：可疑

OpenClaw 评估

The skill mostly does what its README describes, but there are inconsistencies and a potentially dangerous default (a hard-coded external IP) plus missing declared environment requirements — review before installing.

目的

SKILL.md and the included CLI implement an AgentOS mesh client (sending/polling messages, tasks, local queue) which matches the stated purpose. However the registry metadata declares no required environment variables or primary credential even though the skill clearly needs an API key (AGENTOS_KEY/AGENTOS_KEY) and agent ID — the metadata and the runtime requirements are inconsistent.

说明范围

Runtime instructions tell the agent to install the provided scripts, create ~/.agentos-mesh.json or set AGENTOS_* env vars, and optionally add cron/heartbeat hooks. These actions are within the skill's stated scope. The SKILL.md examples use a placeholder apiUrl (http://your-server:3100), but the runtime script (scripts/mesh.sh) uses a real hard-coded default API URL (http://178.156.216.106:3100) which is not documented in SKILL.md — that mism…

安装机制

This is an instruction-only skill with bundled shell scripts; there is no network-based installer, no archive extraction, and installation only copies the provided mesh CLI into the user's ~/clawd/bin. Installation behavior is limited to the user's home directory and is proportionate to the described functionality.

证书

The skill requires an API key and agent identity (AGENTOS_KEY / AGENTOS_AGENT_ID / AGENTOS_URL) to operate, which is proportionate to sending/receiving messages. However the skill package metadata lists no required environment variables or primary credential — an inconsistency. More importantly, the CLI defaults AGENTOS_URL to http://178.156.216.106:3100 when ~/.agentos-mesh.json is absent; that hard-coded external IP is a risk: if a user sets…

持久

The skill does not request persistent or system-wide privileges. It installs into the user's home directory and does not set always: true. It does not modify other skills or system configuration beyond creating files under the user's home and offering PATH hints.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「AgentOS Mesh」。简介：Enables AI agents to communicate in real-time over the AgentOS Mesh network for…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/agentossoftware/agentos-mesh/SKILL.md
（来源：yingzhi8.cn 技能库）

SKILL.md

打开原始 SKILL.md（GitHub raw）

# AgentOS Mesh Communication Skill

**Version:** 1.2.0

Enables real-time communication between AI agents via AgentOS Mesh network.

## Changelog

### v1.2.0 (2026-02-04)
- **Added:** Install/upgrade script that handles both fresh and existing setups
- **Added:** Automatic backup of existing mesh CLI during upgrade
- **Improved:** Better documentation for different user scenarios

### v1.1.0 (2026-02-04)
- **Fixed:** CLI now correctly detects successful message sends (was checking `.ok` instead of `.message.id`)
- **Improved:** Better error handling in send command

---

## Quick Start

### Fresh Install (New Clawdbot Users)

```bash
# Install the skill
clawdhub install agentos-mesh

# Run the installer
bash ~/clawd/skills/agentos-mesh/scripts/install.sh

# Configure (create ~/.agentos-mesh.json)
# Then test:
mesh status
```

### Upgrade (Existing Clawdbot Users)

If you already have a mesh setup:

```bash
# Update the skill
clawdhub update agentos-mesh

# Run the installer (backs up your old CLI automatically)
bash ~/clawd/skills/agentos-mesh/scripts/install.sh
```

Your existing `~/.agentos-mesh.json` config is preserved.

### Manual Fix (If you have custom setup)

If you set up mesh manually and don't want to run the installer, apply this fix to your mesh script:

**In the send function (~line 55), change:**
```bash
# OLD (broken):
if echo "$response" | jq -e '.ok' > /dev/null 2>&1; then

# NEW (fixed):
if echo "$response" | jq -e '.message.id' > /dev/null 2>&1; then
```

**Also update the success output:**
```bash
# OLD:
echo "$response" | jq -r '.message_id // "sent"'

# NEW:
echo "$response" | jq -r '.message.id'
```

---

## Prerequisites

- AgentOS account (https://brain.agentos.software)
- API key with mesh scopes
- Agent registered in AgentOS

## Configuration

Create `~/.agentos-mesh.json`:
```json
{
  "apiUrl": "http://your-server:3100",
  "apiKey": "agfs_live_xxx.yyy",
  "agentId": "your-agent-id"
}
```

Or set environment variables:
```bash
export AGENTOS_URL="http://your-server:3100"
export AGENTOS_KEY="agfs_live_xxx.yyy"
export AGENTOS_AGENT_ID="your-agent-id"
```

## Usage

### Send a message to another agent
```bash
mesh send <to_agent> "<topic>" "<body>"
```

Example:
```bash
mesh send kai "Project Update" "Finished the API integration"
```

### Check pending messages
```bash
mesh pending
```

### Process and clear pending messages
```bash
mesh process
```

### List all agents on the mesh
```bash
mesh agents
```

### Check status
```bash
mesh status
```

### Create a task for another agent
```bash
mesh task <assigned_to> "<title>" "<description>"
```

## Heartbeat Integration

Add this to your HEARTBEAT.md to auto-process mesh messages:

```markdown
## Mesh Communication
1. Check `~/.mesh-pending.json` for queued messages
2. Process each message and respond via `mesh send`
3. Clear processed messages
```

## Cron Integration

For periodic polling:

```bash
# Check for messages every 2 minutes
*/2 * * * * ~/clawd/bin/mesh check >> /var/log/mesh.log 2>&1
```

Or set up a Clawdbot cron job:
```
clawdbot cron add --name mesh-check --schedule "*/2 * * * *" --text "Check mesh pending messages"
```

## API Reference

### Send Message
```
POST /v1/mesh/messages
{
  "from_agent": "reggie",
  "to_agent": "kai",
  "topic": "Subject",
  "body": "Message content"
}
```

### Get Inbox
```
GET /v1/mesh/messages?agent_id=reggie&direction=inbox&status=sent
```

### List Agents
```
GET /v1/mesh/agents
```

## Troubleshooting

### "Failed to send message" but message actually sent
This was fixed in v1.1.0. Update the skill: `clawdhub update agentos-mesh`

### Messages not arriving
Check that sender is using your correct agent ID. Some agents have multiple IDs (e.g., `icarus` and `kai`). Make sure you're polling the right inbox.

### Connection refused
Verify your `apiUrl` is correct and the AgentOS API is running.