aie-model-baseline

aie-model-baseline is an MLOps & model serving skill for AI agents, published by Xilinx in the mlir-aie repository on GitHub. Skillspace rates aie-model-baseline C (70/100) and it passed the safety scan; the rating is based on static analysis only.

Guide to preparing an ML model for AIE/NPU deployment before any device or dataflow work begins — choosing/locking a quantization scheme, exporting ONNX, extracting a deployment manifest (per-op scales/zero-points/shifts/layout), and building a bit-exact numeric oracle. Use this whenever the user is quantizing a model for NPU/AIE deployment, exporting to ONNX, picking an INT8/XINT8 scheme, building a reference/oracle to validate a kernel or dataflow design against, or asking how to start porting a model to run on AIE — even if they haven't mentioned "oracle" or "manifest" by name.

Grade
C
Quality
70 / 100
Safety
Passed
GitHub stars
687

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

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubXilinx/mlir-aie

Our review

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

What the scanner flagged

  • mentions secrets in text

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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