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ops-xperf

AI Cluster Pre-flight Check

by Xperf Inc. · GitHub ↗ · v1.0.1 · MIT-0
linux ⚠ suspicious
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Install in OpenClaw
/install xperf-pre-flight
Description
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...
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install xperf-pre-flight
  3. After installation, invoke the skill by name or use /xperf-pre-flight
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug xperf-pre-flight
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is AI Cluster Pre-flight Check?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 218 downloads so far.

How do I install AI Cluster Pre-flight Check?

Run "/install xperf-pre-flight" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is AI Cluster Pre-flight Check free?

Yes, AI Cluster Pre-flight Check is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does AI Cluster Pre-flight Check support?

AI Cluster Pre-flight Check is cross-platform and runs anywhere OpenClaw / Claude Code is available (linux).

Who created AI Cluster Pre-flight Check?

It is built and maintained by Xperf Inc. (@ops-xperf); the current version is v1.0.1.

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