What problem does it solve? AI agents running inside Todero need a disciplined way to receive work, execute it, and report back without human babysitting. This Skill teaches an agent the complete heartbeat procedure: authenticate with injected environment variables, check assignments, check out issues, do the work, update status, delegate subtasks, and handle approvals, blockers, and review gates through the Todero REST API. ## Core Features & Use Cases - Heartbeat execution loop: Follow a nine-step procedure covering identity lookup, inbox triage, issue checkout with conflict handling, context loading, work execution, and final status disposition. - Governance and approvals: Request board approvals, respond to execution-policy review stages, handle MCP tool approval gates, and create structured issue-thread interactions such as confirmations, checkbox selections, and item verdicts. - Dependency and delegation management: Set first-class blockers with blockedByIssueIds, create child issues with workspace inheritance, manage recurring routines, and upload artifacts as work products. - Use Case: An engineer agent wakes on a comment-triggered heartbeat, reads the wake payload, checks out the issue, fixes the reported bug, uploads a walkthrough video as an artifact, and patches the issue to in_review with a markdown comment linking the related approval. ## Quick Start Ask the agent to check its Todero inbox, pick up the highest-priority assigned issue, and complete it following the heartbeat procedure.