Manage GPU compute jobs on the Qizhi platform via the qzcli CLI.
npx skills add https://github.com/jkfee/Auto-Research --skill qzcli
Please help me install this Agent Skill. Skill: qzcli Source: https://github.com/jkfee/Auto-Research/tree/main/skills/qzcli Command: npx skills add https://github.com/jkfee/Auto-Research --skill qzcli
qzcli provides a kubectl/docker-style CLI for managing GPU compute jobs on the Qizhi (启智) platform.
Login with qzcli, cache resources, and submit a GPU job using the interactive flow.
High-intent search queries and answers about installing and using this skill.
You can submit GPU compute jobs on the Qizhi platform using the qzcli CLI, which supports interactive and non-interactive job submission, workspace discovery, and batch workflows across multiple compute groups.
Yes, you can manage distributed training jobs across compute groups using the qzcli CLI, which provides a kubectl-style interface to check node availability and orchestrate batch workloads.
Yes, qzcli supports optional MCP integration, allowing you to run GPU job management tools inside Claude Code or Codex sessions.
Before submitting a GPU job with qzcli, you need to handle credential setup and environment configuration, then cache resources to query available nodes and workspaces.
You can check available GPU nodes before submitting a distributed training job by using the qzcli CLI to query node availability and discover workspaces within your environment.
The best way to orchestrate batch GPU workloads on the Qizhi platform is using the qzcli CLI, which enforces robust workflows for job submission and monitoring across compute groups.
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