nori-regression
nori-regression is a Model training & evaluation skill for AI agents, published by Synthefy in the synthefy-nori repository on GitHub. Skillspace rates nori-regression C (72/100) and it passed the safety scan; the rating is based on static analysis only.
General tabular regression with Nori, the Synthefy tabular foundation model — sklearn-style in-context fit/predict with zero training, native prediction intervals (quantiles / full predictive distribution), honest baseline comparison under a fixed CV protocol, and SHAP / PDP / feature-selection interpretability — plus leak-safe one-step time-series forecasting via lag features and a rolling-origin backtest. Use when predicting a continuous target from tabular features, when you need uncertainty bands without extra machinery, when forecasting a single series one step ahead, or when the dataset is too small to train a model on.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 31
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
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 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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