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AF nemotron-customize

Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 3 906 tokens Open the sourceclawhub.ai↗ analyzed 30 h ago

Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or…

As a process F 52/100 · Will not run — References files that are not bundled: references/CATALOG.md, references/ARTIFACTS.md, references/COMMANDS.md

ProcedureInfrastructureSoftware developmentWriting and documentstype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
52/100
Will not run
References files that are not bundled: references/CATALOG.md, references/ARTIFACTS.md, references/COMMANDS.md
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
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/CATALOG.md
  • warning missing-ref reference to a missing file: references/ARTIFACTS.md
  • warning missing-ref reference to a missing file: references/COMMANDS.md
  • warning missing-ref reference to a missing file: references/HARDWARE.md
  • warning missing-ref reference to a missing file: references/PATTERNS.md
  • warning missing-ref reference to a missing file: references/WORKFLOW.md
  • warning missing-ref reference to a missing file: references/context/index.toml
  • warning missing-ref reference to a missing file: references/act/PROJECT.md
  • warning missing-ref reference to a missing file: references/act/STAGE.md

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: references/CATALOG.md, references/ARTIFACTS.md, references/COMMANDS.md
  • 0Tools and files. 9 referenced file(s) missing: references/CATALOG.md, references/ARTIFACTS.md, references/COMMANDS.md
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 6 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 64 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 3906 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (9 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 664: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 64 items
  • +4Has examples (0 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.