Query the Clade monitor for loop, session, cost, and commit status.
npx skills add https://github.com/shenxingy/Clade --skill clade-status
Please help me install this Agent Skill. Skill: clade-status Source: https://github.com/shenxingy/Clade/tree/main/adapters/openclaw/skills/clade-status Command: npx skills add https://github.com/shenxingy/Clade --skill clade-status
This Skill helps you quickly understand what Clade is doing in an autonomous coding loop—without guessing—so you can spot blockers, track convergence, and review recent activity.
Ask an AI to check the current Clade status for your project by calling the GET /status endpoint using your CLADE_BASE_URL and CLADE_API_KEY.
High-intent search queries and answers about installing and using this skill.
Check autonomous coding loop progress by requesting the Clade monitor status endpoint, which returns structured data on iteration number, convergence status, and the active goal.
Track session status and worker activity by querying the Clade monitor's status endpoint, which returns structured data on running sessions, outer iteration, and current mode during unattended runs.
Check API costs and recent git commits by requesting the Clade status endpoint, which provides structured data summarizing total cost, last-iteration cost, and recent repository commits.
Yes, querying Clade monitor status requires a CLADE_API_KEY for Bearer authentication and a CLADE_BASE_URL to send the GET request to the remote status endpoint.
Yes, you can scope status monitoring to a specific project by including an optional project query parameter in the GET request to the Clade monitor status endpoint.
Use a remote monitor for autonomous coding tasks when you need real-time visibility into running workers, ongoing tasks, and latest repository activity during unattended runs without manual inspection.
shenxingyStart, stop, or clear blockers for Clade autonomous coding loops via a control endpoint.
geblQuery Claude-Vis to analyze session costs, token usage, and activity logs.
alexanderopCommit staged changes and push to a remote Git repository.
tiancaiamaoA data-driven approach to privacy-preserving ML: balancing the trade-off between privacy and performance through synthetic data generation and algorithmic sandboxing.
