day0-release

day0-release is an MLOps & model serving skill for AI agents, published by NVIDIA in the Model-Optimizer repository on GitHub. Skillspace rates day0-release F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.

Deterministic end-to-end driver for day-0 quantized-checkpoint releases — chains PTQ → evaluation → comparison with enforced gates between stages (the evaluation stage deploys the checkpoint itself), and returns a publish decision (ACCEPT / REGRESSION / ANOMALOUS / INFEASIBLE). Use when the user asks to "release a model at day-0", "quantize and validate model X is within N% of baseline and tell me if it's publishable", or "run the full day-0 workflow". Do NOT use for single-stage requests — quantizing only (use ptq), serving only (use deployment), evaluating only (use evaluation), or comparing two existing runs (use compare-results).

Grade
F
Quality
45 / 100
Safety
Risky
GitHub stars
3,797

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since.

View source on GitHubNVIDIA/Model-Optimizer

Our review

Architecture
96 / 100
Maturity
Basic: a single SKILL.md
Security scan
High-risk patterns
License
Not declared. Check the repository before reusing it.

What the scanner flagged

  • dynamic code execution (eval/exec)

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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