What problem does it solve? Submitting, monitoring, and stopping distributed GPU training jobs on the Qizhi (启智) platform normally requires manual web console work; this Skill wraps the qzcli CLI so jobs, workspaces, and compute groups can be managed from the command line or an AI agent. ## Core Features & Use Cases - Job Lifecycle Management: Login, discover workspaces and compute groups, check available GPU nodes, submit jobs interactively or non-interactively, and stop or watch running jobs. - Batch & Matrix Submission: Submit Cartesian-product job sweeps from a JSON config with name and command templates, plus Slurm-based HPC/CPU job support. - MCP Integration: Expose qzcli as an MCP tool so Claude Code or Codex can manage jobs directly. - Use Case: A researcher needs to evaluate a model at four checkpoints across two steps. They run qzcli res -u to refresh the workspace cache, then qzcli batch batch_config.json --dry-run to preview eight jobs before submitting them with a 3-second delay between submissions. ## Quick Start Ask the assistant to log in to the Qizhi platform with qzcli, refresh the workspace resource cache, and list currently running jobs.