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BF nvflare-convert-pytorch

Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use when the user names plain PyTorch or preliminary source inspection identifies one plain-PyTorch owner, and not for Lightning, other frameworks, deployment, POC/production lifecycle, or experiment workflows.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 2 461 tokens Open the sourceclawhub.ai↗ analyzed 14 h ago

Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use…

As a process F 50/100 · Will not run — References files that are not bundled: references/recipe-selection.md, references/pytorch-client-api-conversion.md, references/job-validation.md

GeneratorSoftware developmentInfrastructureData 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
F
50/100
Will not run
References files that are not bundled: references/recipe-selection.md, references/pytorch-client-api-conversion.md, references/job-validation.md
Tools and files w 18
0
Result and completion w 14
0
Failures and branches w 10
0
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: references/recipe-selection.md
  • warning missing-ref reference to a missing file: references/pytorch-client-api-conversion.md
  • warning missing-ref reference to a missing file: references/job-validation.md

Process rating: all ten parameters 50/100

Will not run. References files that are not bundled: references/recipe-selection.md, references/pytorch-client-api-conversion.md, references/job-validation.md
  • 0Tools and files. 3 referenced file(s) missing: references/recipe-selection.md, references/pytorch-client-api-conversion.md, references/job-validation.md
  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 25 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2461 tokens

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
  • +4No input/output examples
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 362: enough signal without eating the budget
  • +4Structure: 5 headings
  • +3Step-by-step instructions: 25 items
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.