getitune-preparing-datasets
getitune-preparing-datasets is a Model training & evaluation skill for AI agents, published by open-edge-platform in the geti repository on GitHub. Skillspace rates getitune-preparing-datasets D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Prepare and point datasets at the getitune library (the Geti training library) for training, testing, and prediction. Use when a user asks which dataset formats are supported, how the `data=` argument of `create_engine(...)` / `--data_root` works, why format auto-detection fails, how to lay out COCO/YOLO/Pascal VOC/Datumaro-native data, how to use a zip archive, or how to pass an Ultralytics YOLO `data.yaml`. Covers Datumaro-based auto-detection and per-task data expectations.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 1,267
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, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Explains dataset input formats for the public getitune library
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.