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AF tao-setup-nvidia-gpu-host

Host setup for TAO GPU backends. Checks and, after user approval, installs minimum-compatible NVIDIA driver, CUDA Toolkit, and NVIDIA Container Toolkit versions for Docker/local-Docker and Kubernetes GPU worker hosts. TAO-wide defaults can be overridden by the selected model's runtime profile. The `--check-only` path works on any Linux distribution; `--install` automates debian-family (Ubuntu/Debian/Pop!_OS/Mint/Zorin/Raspbian), rhel-family (Fedora/RHEL/Rocky/AlmaLinux), and suse-family (openSUSE/SLES) hosts, and prints actionable manual-install steps for everything else. Use when the user asks to "set up an NVIDIA GPU host", "check TAO Docker GPU runtime", or prepare a Kubernetes GPU worker for TAO.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 2 842 tokens Open the sourceclawhub.ai↗ analyzed 15 h ago

Host setup for TAO GPU backends.

As a process F 48/100 · Will not run — References files that are not bundled: references/skill_info.yaml

ProcedureDockerKubernetesInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
94
Quality 40%
84
Run on models
none yet
Process rating
F
48/100
Will not run
References files that are not bundled: references/skill_info.yaml
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Bash
  • low Secrets in code secret-high-entropy-token SKILL.md:156
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Driver | current `nvidia-open` (override: `$NVIDIA_DRIVER_PACKAGE_DEBIAN`) | current `nvidia-driver-cuda`, `kmod-nvidia-open-dkms` (override: `$NVIDIA_DRIVER_PACKAGE_RHEL`, `$NVIDIA_DRIVER_KMOD_RHEL
    table

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/skill_info.yaml

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: references/skill_info.yaml
  • 0Tools and files. 1 referenced file(s) missing: references/skill_info.yaml
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 1 mutating operations with no state check
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 14 steps, 1 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2842 tokens
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 709: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (5 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.