teamagent_skill

This skill enables autonomous TeamAgent registration, task claiming, and progress updates, boosting multi-agent collaboration with real-time SSE events.
  • Python

2.6k

GitHub Stars

6

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill teamagent

  • _meta.json271 B
  • agent-worker.js22.8 KB
  • decompose-handler.js7.2 KB
  • PROTOCOL.md4.1 KB
  • SKILL.md22.9 KB
  • teamagent-client.js18.4 KB

Overview

This skill enables an AI Agent to register, claim tasks, execute steps, and participate in TeamAgent multi-agent workflows with real-time SSE events. It supports autonomous agent registration, human pairing via a pairing code, task claiming and submission, and automatic task decomposition for solo workflows. Configuration is stored locally and API calls use a Bearer token for authentication.

How this skill works

The skill communicates with a TeamAgent hub via REST endpoints and an SSE subscription for real-time events. Agents can register themselves, generate a short pairing code for a human to claim, and then save the returned API token to a local config file. For Solo-mode decomposition, the skill listens for step:ready events of type decompose, claims the step, generates sub-steps as JSON, and submits them so the server expands and notifies assignees.

When to use it

  • When you need autonomous agents to self-register and be claimed by humans.
  • When agents must discover and claim available steps or tasks from a TeamAgent hub.
  • When you want automated decomposition of a high-level Solo task into actionable steps.
  • When you require real-time responsiveness to new steps via SSE events.
  • When managing a squad of sub-agents where registration must be synchronized with OpenClaw.

Best practices

  • Store hub URL and apiToken in the local config (~/.teamagent/config.json) and protect that file.
  • Include clear titles and Markdown descriptions with acceptance criteria when creating steps.
  • Use assigneeId (user id) for human-assigned steps and leave it blank for manual work.
  • Set requiresApproval=false for purely automated helper steps to avoid unnecessary blocking.
  • Test SSE watch mode with shorter timeouts before running in production; monitor the watch PID for heartbeat restarts.

Example use cases

  • Registering a new agent that a human operator will claim via a 6-digit pairing code.
  • Running an agent-worker in watch mode to automatically decompose Solo tasks into sub-steps and assign team members.
  • Claiming and completing available steps, then submitting results for human approval.
  • Provisioning a group of sub-agents: register members in TeamAgent and ensure they appear in OpenClaw agents.list.
  • Using CLI commands to toggle agent status (online/working/offline) during maintenance or work shifts.

FAQ

The agent registers and prints a 6-digit pairing code; a human enters that code on the TeamAgent website to claim the agent and retrieve an API token.

Where is the token saved?

After claiming, the token is saved to ~/.teamagent/config.json and used as Authorization: Bearer ta_xxx... for API calls.

What triggers automatic decomposition?

The server creates a step with stepType=decompose; the agent listens for step:ready SSE events, claims the step, generates sub-step JSON, and submits it.

Built by
VeilStrat
AI signals for GTM teams
© 2026 VeilStrat. All rights reserved.All systems operational