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BF jetson-llm-benchmark

Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 2 975 tokens Open the sourceclawhub.ai↗ analyzed 26 h ago

Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.

As a process F 67/100 · Will not run — References files that are not bundled: scripts/bench_vllm.sh, scripts/bench_llama_cpp.sh, scripts/bench_ollama.sh

ProcedureAI and agentsData and analyticstype 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
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
F
67/100
Will not run
References files that are not bundled: scripts/bench_vllm.sh, scripts/bench_llama_cpp.sh, scripts/bench_ollama.sh
Tools and files w 18
0
When it triggers w 12
50
Result and completion w 14
60
the three weakest of ten parameters · all ten

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 · 0

✓ No critical or high findings

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: scripts/bench_vllm.sh
  • warning missing-ref reference to a missing file: scripts/bench_llama_cpp.sh
  • warning missing-ref reference to a missing file: scripts/bench_ollama.sh

Process rating: all ten parameters 67/100

Will not run. References files that are not bundled: scripts/bench_vllm.sh, scripts/bench_llama_cpp.sh, scripts/bench_ollama.sh
  • 0Tools and files. 3 referenced file(s) missing: scripts/bench_vllm.sh, scripts/bench_llama_cpp.sh, scripts/bench_ollama.sh
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 32 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2975 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 13 top-level sections: this looks like several domains in one skill

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 108: 120–800 characters recommended
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 32 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.