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AI Cluster Pre-flight Check

作者 Xperf Inc. · GitHub ↗ · v1.0.1 · MIT-0
linux ⚠ suspicious
218
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在 OpenClaw 中安装
/install xperf-pre-flight
功能描述
Pre-flight check for GPU cluster nodes — node validation before training, check cluster node health, is my GPU node ready. 26 health checks covering GPU, PCI...
安全使用建议
This skill appears to do what it claims (local and cross‑node hardware/config checks), but take precautions before running it on production hosts: - Run it in a safe environment first (a non‑production node or an isolated VM) to observe behavior. - Be aware it may require root for full coverage (dmidecode, setpci, ipmitool, reading /dev/mem, etc.). Without root some checks will fail or be skipped. - Cross‑node checks (PREFLIGHT_PEER_IPS) will attempt SSH to the IPs you supply; those are outbound connections from the node. If you set SWITCH_HOST or similar it may attempt SSH to switches. - The script will run docker run with public vendor images (nvidia/cuda, rocm images). That will pull and execute container code from registries — review those image names and ensure pulling external images is acceptable in your environment. - The manifest under‑declares some runtime binaries (ssh, ip, lspci, ethtool, setpci, dmidecode, ipmitool, docker). Ensure required tooling is present and acceptable. - PREFLIGHT_NODE_ID is not a secret; the registry's labeling as a primary credential is misleading. If you want to proceed: review the bundled scripts (they are included), run with PREFLIGHT_PEER_IPS unset (local checks only) and without PREFLIGHT_STRICT first, and consider auditing or removing the docker tests if pulling/executing images is unacceptable in your environment.
功能分析
Type: OpenClaw Skill Name: xperf-pre-flight Version: 1.0.1 The skill bundle contains several high-risk shell injection vulnerabilities in 'lib/checks.sh'. Specifically, 'check_1_25' uses 'eval' on the 'SWITCH_CLI_CMD' environment variable, and 'check_1_1', 'check_1_26', and 'check_mesh_ping' execute 'ssh' and 'ping' commands using unsanitized input from 'PREFLIGHT_PEER_IPS'. While these functions are aligned with the stated purpose of GPU cluster validation, the lack of input sanitization allows for arbitrary command execution if the environment variables are manipulated. No evidence of intentional malice or data exfiltration was observed.
能力评估
Purpose & Capability
The name/description match the included scripts: the code implements ~26 local and cross‑node hardware and config checks (GPU, PCIe, RDMA, NUMA, firewall, BIOS, switch, etc.). Required binaries (GPU vendor tools) are appropriate. However the manifest under‑declares other binaries the scripts use (ssh, ip, lspci, ethtool, setpci, dmidecode, ipmitool, docker, etc.), and declares jq as a required binary although the scripts implement JSON formatting without jq. Also the registry marks PREFLIGHT_NODE_ID as the "primary credential" despite it being a harmless node identifier.
Instruction Scope
Runtime instructions (run preflight.sh) are explicit and the scripts do many privileged/local inspections: reading /proc/cmdline, /sys entries, lspci, lsmod, setpci, dmidecode, ipmitool, ip/ethtool, and more. Cross‑node checks will attempt SSH to the IPs you provide. The script also runs docker run for vendor test images (nvidia/cuda, rocm/*) which will pull and execute container images from the network. These behaviors are coherent with the stated purpose but amount to network activity and code execution on the host (docker images) and attempts to access low‑level system interfaces that may require root. The SKILL.md does not explicitly warn about pulling/running container images or requiring root privileges for some checks.
Install Mechanism
No install spec — bundled as scripts. That keeps install risk low (no arbitrary archive download during install). Files are present in the skill package, so nothing is fetched during install; however runtime docker actions may fetch images from registries.
Credentials
No sensitive credentials are required. The primaryEnv is PREFLIGHT_NODE_ID which is just an identifier. The skill exposes many optional environment variables (PREFLIGHT_PEER_IPS, SWITCH_HOST, SWITCH_CLI_CMD, SWITCH_USER, etc.) which are relevant to cross‑node and switch checks. Nothing requests unrelated cloud/API credentials. However the registry's labeling of PREFLIGHT_NODE_ID as a "primary credential" is misleading.
Persistence & Privilege
always is false and the skill does not request permanent presence or modify other skills. It can be invoked autonomously (default) which is normal — note this combined with network and docker execution increases operational impact, but autonomy alone is not flagged.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install xperf-pre-flight
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /xperf-pre-flight 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
xperf-pre-flight 1.0.1 - Added an "Example Prompts" section to improve usability and show natural prompt phrasing. - Updated the description for greater clarity and keyword coverage, especially for users seeking pre-flight checks for GPU cluster nodes. - No code or functional changes; documentation enhancements only.
v1.0.0
AI Cluster Pre-flight Check v1.0.0 — Initial release - Provides 26 comprehensive GPU cluster node health checks covering hardware, networking, and software readiness. - Auto-detects GPU vendor (NVIDIA/AMD) and network type (InfiniBand/RoCE/Ethernet). - Offers flexible check selection, strict mode, and cross-node validation via environment variables. - Outputs JSON results for easy integration and diagnostics. - Designed for bare-metal cluster readiness, ongoing health monitoring, and troubleshooting. - Includes clear check catalog, usage instructions, and support contacts.
元数据
Slug xperf-pre-flight
版本 1.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

AI Cluster Pre-flight Check 是什么?

Pre-flight check for GPU cluster nodes — node validation before training, check cluster node health, is my GPU node ready. 26 health checks covering GPU, PCI... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 218 次。

如何安装 AI Cluster Pre-flight Check?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install xperf-pre-flight」即可一键安装,无需额外配置。

AI Cluster Pre-flight Check 是免费的吗?

是的,AI Cluster Pre-flight Check 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

AI Cluster Pre-flight Check 支持哪些平台?

AI Cluster Pre-flight Check 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux)。

谁开发了 AI Cluster Pre-flight Check?

由 Xperf Inc.(@ops-xperf)开发并维护,当前版本 v1.0.1。

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