agent-team-mesh

agent-team-mesh is a skill for Claude Code, Codex from Songhonglei/better-agent-skills. It costs 185 tokens per session (2,048 once invoked), scanned B, original, MIT.

A direct WebSocket communication mesh for OpenClaw agents running in separate containers or Kubernetes pods. Agents contact one another directly without a broker or central server.

In plain words
What is it for?
Use it for peer-to-peer agent communication across a routable network, including Kubernetes environments where pod IPs are used.
Why use it?
It lets distributed agents discover teammates, exchange messages, wait for replies, and review message history while using separate authentication tokens.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it for peer-to-peer agent communication across a routable network, including Kubernetes environments where pod IPs are used.

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Install with agentmods
npx agentmods add skills/songhonglei/better-agent-skills/agent-team-mesh
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Songhonglei/better-agent-skills --skill agent-team-mesh
Clone the repo
git clone --depth 1 https://github.com/Songhonglei/better-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agent-team-mesh

README.md
[![agentmods](https://agentmods.dev/badge/skills/songhonglei/better-agent-skills/agent-team-mesh/github.svg)](https://agentmods.dev/skills/songhonglei/better-agent-skills/agent-team-mesh)
Your own site
<a href="https://agentmods.dev/skills/songhonglei/better-agent-skills/agent-team-mesh"><img src="https://agentmods.dev/badge/skills/songhonglei/better-agent-skills/agent-team-mesh/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agent-team-mesh

Your own site · 80×15
<a href="https://agentmods.dev/skills/songhonglei/better-agent-skills/agent-team-mesh"><img src="https://agentmods.dev/badge/skills/songhonglei/better-agent-skills/agent-team-mesh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 185 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,048 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00185 $0.02048
Opus 5 $0.00093 $0.01024
Sonnet 5 $0.00037 $0.00410
Haiku 4.5 $0.00018 $0.00205

Measured 11d ago against content hash 2b9149cd8875, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade B, and why

agent-team-mesh scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent-mesh.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

chmod 600 file, not committed to git), message size limits (4KB warn /

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Python 3.8+, bash, curl, openclaw CLI on PATH
skills/agent-team-mesh/SKILL.md · 230 lines

How it starts

The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.

agent-team-mesh

Team-wide P2P mesh for OpenClaw agents running on different containers/pods. Direct WebSocket calls between teammates' agents — no broker, no central database.

Open-source edition of an internal team-comms skill, rebuilt with proper token hygiene, message size limits, dry-run mode, and pluggable identity detection.


Architecture

My agent's Gateway (WS)
   │
   ▼
ws://<teammate's pod IP>:18789  ──▶  Teammate's agent processes message
   │  (token-authenticated)         and writes a reply to their session
   ▼
chat.send → agent.wait → chat.history
  • No broker — direct P2P, each teammate's OpenClaw Gateway is the endpoint
  • Per-agent tokens — each agent has its own WS token (not a shared key)
  • Pod IP direct — Kubernetes hostname/DNS sometimes doesn't cross nodes
  • IP usually stable — long-running pods, but use sync if they roll

Prerequisites

  • All agents on a routable network (same VPC / mesh / VPN)
  • Each agent's OpenClaw Gateway exposed on port :18789 over WebSocket
  • Per-agent WS tokens collected and stored in tokens.json (chmod 600)
  • OPENCLAW_ALLOW_INSECURE_PRIVATE_WS=1 is set by the script (ws:// plaintext is acceptable only on trusted internal networks)
  • Python 3.8+, bash, curl, openclaw CLI on PATH

Setup

1. Edit your team registry

Copy references/registry.json and fill in your teammates:

{
  "agents": [
    { "name": "Alice", "emailPrefix": "alice", "ip": "10.0.0.10", "hostname": "agent-alice-0" },
    { "name": "Bob",   "emailPrefix": "bob",   "ip": "10.0.0.11", "hostname": "agent-bob-0" }
  ]
}

The emailPrefix is the key — it must match what whoami detects on each teammate's machine.

2. Create tokens file

Each teammate generates their own OpenClaw gateway WS token and shares it. Collect into:

Read the full file on GitHub · 230 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 230 lines · 185 tokens per session scan B 2b9149cd8875

Subscribe to this mod's changes

agent-team-mesh is a skill published in the GitHub repository Songhonglei/better-agent-skills (3 stars, last pushed 4d ago), licensed MIT. It adds 185 tokens to every session and 2,048 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.