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AF physical-ai-neural-reconstruction

Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, carline adaptation, PhysicalAI HF datasets. Do NOT use for SimReady or infra setup.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 4 826 tokens Open the sourceclawhub.ai↗ analyzed 29 h ago

Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, carline adaptation, PhysicalAI HF datasets.

As a process F 58/100 · Will not run — References files that are not bundled: references/secrets-handling.md, references/workflows.md, references/mix-ups.md

ProcedureDockerGitHubData 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%
99
Quality 40%
76
Run on models
none yet
Process rating
F
58/100
Will not run
References files that are not bundled: references/secrets-handling.md, references/workflows.md, references/mix-ups.md
Tools and files w 18
0
Result and completion w 14
0
Running it twice w 4
30
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 · 1

✓ No critical or high findings

Medium and low: 1

✓ Guard found no suspicious behaviour. 1 matches are attack strings quoted in this security skill's own documentation.

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/secrets-handling.md
  • warning missing-ref reference to a missing file: references/workflows.md
  • warning missing-ref reference to a missing file: references/mix-ups.md
  • warning missing-ref reference to a missing file: references/upstream-fetch.md
  • warning missing-ref reference to a missing file: references/maintenance.md
  • warning missing-ref reference to a missing file: references/teardown.md
  • warning missing-ref reference to a missing file: references/ngc-and-registry.md
  • warning missing-ref reference to a missing file: scripts/validate_setup.py
  • note frontmatter-key unknown frontmatter key "tools"
  • note edit-residue the text marks something as outdated (lines 252, 312): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 58/100

Will not run. References files that are not bundled: references/secrets-handling.md, references/workflows.md, references/mix-ups.md
  • 0Tools and files. 8 referenced file(s) missing: references/secrets-handling.md, references/workflows.md, references/mix-ups.md
  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 5 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4826 tokens
  • 85Steps. 50 steps, 2 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (6 tags): a typed call is more reliable

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
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 169: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 50 items
  • +4Has examples (3 code blocks)
  • +1License stated

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