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AF jetson-memory-audit

Measure Jetson DRAM/NvMap usage and verify before/after memory reclamation with live audit data.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 2 202 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Measure Jetson DRAM/NvMap usage and verify before/after memory reclamation with live audit data.

As a process F 56/100 · Will not run — References files that are not bundled: scripts/audit.sh, scripts/drop_caches.sh

AnalyzerData 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
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
F
56/100
Will not run
References files that are not bundled: scripts/audit.sh, scripts/drop_caches.sh
Tools and files w 18
0
Progress reporting w 2
0
When it triggers w 12
20
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/audit.sh
  • warning missing-ref reference to a missing file: scripts/drop_caches.sh

Process rating: all ten parameters 56/100

Will not run. References files that are not bundled: scripts/audit.sh, scripts/drop_caches.sh
  • 0Tools and files. 2 referenced file(s) missing: scripts/audit.sh, scripts/drop_caches.sh
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 14 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 27 steps, 1 vague phrases
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2202 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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 96: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 27 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.