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NVIDIA/Model-OptimizerSkill

Establish baseline-vs-candidate evaluation plans, delegate missing evaluations, compare validated results, and decide quantization feasibility. Use when the user asks to compare baseline vs quantized runs, explain an accuracy drop/regression, verify whether a quantized checkpoint is acceptable, or compare NEL/MLflow evaluation outputs. Do NOT use for generic single-model evaluation without comparison intent (use evaluation), live NEL status/debugging (use launching-evals), or generic MLflow browsing without a comparison goal (use accessing-mlflow).

ScannedSkillSource: GitHub
5,374 stars +87 this week Updated 16d ago License Apache-2.0 Context ≈143 tokens always loaded
77popular

Why this score

Stars19/35
Usage (forks)8/15
Upkeep25/25
License15/15
Owner history10/10

This repo hosts 10 skills, so its 5,374 stars are split between them (about 537 each) for scoring.

Popularity score: 77/100 from public GitHub signals only. It shows how widely used and maintained this is, not how well it works. Not included yet: the fake-star check. The security scan is shown separately and doesn't change the score. How we rank

Security

Scanned Oct 21, 2026 at commit f1d68fd4dd50, with Cisco's open-source skill-scanner.

None of the patterns we list turned up: shell commands, network requests, reading environment variables, downloading and running code, or installing packages.

A scan lists patterns in the code. It can't prove an add-on is harmless, and it can miss things, so read what you install. How we scan

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