AgentOS Mesh Communication Skill

**Version:** 1.2.0

7 stars

Best use case

AgentOS Mesh Communication Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

**Version:** 1.2.0

Teams using AgentOS Mesh Communication Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/agentos-mesh/SKILL.md --create-dirs "https://raw.githubusercontent.com/Demerzels-lab/elsamultiskillagent/main/public/skills/agentossoftware/agentos-mesh/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/agentos-mesh/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How AgentOS Mesh Communication Skill Compares

Feature / Agent	AgentOS Mesh Communication Skill	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

**Version:** 1.2.0

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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.

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