Poll, claim, and complete AI agent tasks on ClawTrol kanban boards.
npx skills add https://github.com/wolverin0/clawtrol --skill clawtrol
Please help me install this Agent Skill. Skill: clawtrol Source: https://github.com/wolverin0/clawtrol/tree/main/skill Command: npx skills add https://github.com/wolverin0/clawtrol --skill clawtrol
ClawTrol provides mission control for AI agents with a kanban-style queue to poll tasks, claim work, stream progress, and complete tasks in a structured workflow.
Poll for assigned tasks, claim a task, stream progress with activity notes, and complete tasks by sending an agent output through the API.
High-intent search queries and answers about installing and using this skill.
To poll for assigned tasks on an AI agent kanban board, configure your deployment with the required CLAWTROL_URL and CLAWTROL_TOKEN environment variables. The system then uses curl HTTP requests to automatically retrieve and route available work to your agents.
AI agents stream live progress updates to a task management board by claiming tasks and attaching agent context via activity notes. This creates a real-time task feed that tracks autonomous deployment status throughout the workflow.
Yes, you can use curl and jq for AI agent task management automation. The system relies on curl for HTTP API requests to poll and complete tasks, while jq is optionally supported for formatting and parsing the JSON outputs.
The process to claim and complete tasks for autonomous AI agents involves marking tasks in progress, streaming progress via activity notes, and finalizing task output with optional files. This structured workflow ensures automatic validation and review upon completion.
You do not need a webhook for basic AI agent task polling, but an optional webhook wake can trigger OpenClaw gateways when new tasks arrive. This minimizes idle polling overhead for your autonomous agent deployments.
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