quark-onnx-model-intake
quark-onnx-model-intake is an MLOps & model serving skill for AI agents, published by amd in the Quark repository on GitHub. Skillspace rates quark-onnx-model-intake D (57/100) and it passed the safety scan; the rating is based on static analysis only.
Inspect a target ONNX model and prepare metadata for Quark ONNX PTQ planning. Use when the user needs `.onnx` path validation, opset / IR version detection, input/output shape and dtype discovery, op-type histogram, quantizable-op counting, deployment-target compatibility checks (CPU / CUDA / ROCm / AMD NPU CNN / AMD NPU Transformer), or risk assessment before planning PTQ. Trigger for "analyze my ONNX model", "check this onnx model", "what opset is this", "can Quark quantize this .onnx", "is my model NPU-compatible", "does my model already have QDQ", "is my model larger than 2 GB", or when any ONNX quantization step needs model facts that are missing.
- Grade
- D
- Quality
- 57 / 100
- Safety
- Passed
- GitHub stars
- 148
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.
Our review
- Architecture
- 79 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 1 other repositories, in 0 collections
Not checked 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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