Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Communication & Collaboration
AgentOS Mesh
Enables AI agents to communicate in real-time over the AgentOS Mesh network for sending messages, tasks, and status updates.
skill openclawclawhub Free
Enables AI agents to communicate in real-time over the AgentOS Mesh network for sending messages, tasks, and status updates.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/install.sh, scripts/mesh.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.3.0
Provenance
- Publisher
- AgentOSsoftware
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
AgentOS Mesh Communication Skill
Version: 1.2.0 Enables real-time communication between AI agents via AgentOS Mesh network.
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
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
AgentOS account (https://brain.agentos.software) API key with mesh scopes Agent registered in AgentOS
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"
Send a message to another agent
mesh send <to_agent> "<topic>" "<body>" 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 <assigned_to> "<title>" "<description>"
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"
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
"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.
Category context
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Scripts1 Docs
- SKILL.md
- scripts/install.sh
- scripts/mesh.sh