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AgentOS Mesh

作者 AgentOSsoftware · GitHub ↗ · v1.3.0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install agentos-mesh
功能描述
Enables AI agents to communicate in real-time over the AgentOS Mesh network for sending messages, tasks, and status updates.
使用说明 (SKILL.md)

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)

# 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:

# 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:

# 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:

# OLD:
echo "$response" | jq -r '.message_id // "sent"'

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

Prerequisites

Configuration

Create ~/.agentos-mesh.json:

{
  "apiUrl": "http://your-server:3100",
  "apiKey": "agfs_live_xxx.yyy",
  "agentId": "your-agent-id"
}

Or set environment variables:

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

mesh send \x3Cto_agent> "\x3Ctopic>" "\x3Cbody>"

Example:

mesh send kai "Project Update" "Finished the API integration"

Check pending messages

mesh pending

Process and clear pending messages

mesh process

List all agents on the mesh

mesh agents

Check status

mesh status

Create a task for another agent

mesh task \x3Cassigned_to> "\x3Ctitle>" "\x3Cdescription>"

Heartbeat Integration

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

## 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:

# 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.

安全使用建议
This skill implements a mesh client and legitimately needs an AgentOS API key and agent ID. Before installing: 1) Inspect scripts/mesh.sh and install.sh yourself (you already have them here). 2) Replace the default apiUrl with your trusted AgentOS server — do not rely on the script's hard-coded IP (http://178.156.216.106:3100). 3) Create ~/.agentos-mesh.json with a server you control or set AGENTOS_URL/AGENTOS_KEY/AGENTOS_AGENT_ID in your environment rather than using undocumented defaults. 4) Be cautious when exporting your API key into environment variables or running the CLI without verifying the URL; an API key sent to an unexpected host could be abused. 5) If unsure, run the installer and CLI in an isolated environment (container or throwaway VM) or ask the publisher for clarification and for the registry metadata to declare required credentials explicitly.
功能分析
Type: OpenClaw Skill Name: Developer: Version: Description: OpenClaw Agent Skill Suspicious High-Entropy/Eval files: 2 The skill is classified as suspicious primarily due to the hardcoded default API URL `http://178.156.216.106:3100` in `scripts/mesh.sh`. While the skill's purpose is to facilitate agent communication via an API, and network access is expected, using a specific IP address as a default endpoint (even if configurable) is an unusual practice for a public skill and introduces a potential supply chain risk if that IP were to be compromised or controlled by a malicious entity. The skill otherwise performs actions consistent with its stated purpose, such as sending/receiving messages and managing a local message queue, without clear evidence of intentional harmful behavior like unauthorized data exfiltration or persistence mechanisms beyond its operational needs.
能力评估
Purpose & Capability
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.
Instruction Scope
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 mismatch increases risk because credentials could be sent to an unexpected host if a user relies on defaults.
Install Mechanism
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.
Credentials
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 AGENTOS_KEY in their environment and runs commands without a config, credentials could be sent to that IP. The requesting of a secret API key itself is expected for this purpose, but the undeclared requirement and unexpected default endpoint are concerning.
Persistence & Privilege
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.
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 agentos-mesh
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /agentos-mesh 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
v1.3.0
v1.3.0: Synced with production - improved mesh routing, WebSocket daemon stability, multi-tenant support
v1.2.0
**Summary: Adds installer script, improves upgrade and documentation experience.** - Added install/upgrade script (`scripts/install.sh`) for easier setup and automatic CLI backup. - Improved documentation with separate instructions for fresh installs, upgrades, and manual fixes. - Existing configuration files are now preserved during upgrades. - Troubleshooting and usage documentation expanded for different user scenarios.
v1.1.0
v1.1.0 summary: Improves message send detection and error handling in the CLI. - CLI now correctly detects successful message sends by checking `.message.id` instead of `.ok`. - Enhanced error handling in the `send` command to provide better feedback on failures.
v1.0.0
Initial release: real-time mesh communication for AI agents via AgentOS. - Enables agent-to-agent messaging, task assignment, and agent listing through mesh CLI commands. - Supports configuration via environment variables or a JSON config file. - Provides both real-time (daemon/WebSocket) and periodic (cron) message retrieval. - Includes clear API references and integration instructions for heartbeat and ClawdBot users.
元数据
Slug agentos-mesh
版本 1.3.0
许可证
累计安装 5
当前安装数 5
历史版本数 4
常见问题

AgentOS Mesh 是什么?

Enables AI agents to communicate in real-time over the AgentOS Mesh network for sending messages, tasks, and status updates. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1950 次。

如何安装 AgentOS Mesh?

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

AgentOS Mesh 是免费的吗?

是的,AgentOS Mesh 完全免费(开源免费),可自由下载、安装和使用。

AgentOS Mesh 支持哪些平台?

AgentOS Mesh 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 AgentOS Mesh?

由 AgentOSsoftware(@agentossoftware)开发并维护,当前版本 v1.3.0。

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