"Routes scikit-plot requests for metric curves, estimator
Scanned 9/9/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill scikit-plot --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: "scikit-plot"
description: "Routes scikit-plot requests for metric curves, estimator
diagnostics, clustering elbow plots, PCA visualizations, and legacy factory
compatibility."
disable-model-invocation: true
metadata:
disco-role: operating
license: MIT
---
# scikit-plot
Use this root skill when the task is about the `scikitplot` plotting library itself: confusion matrices, ROC and precision-recall curves, KS statistics, calibration curves, cumulative gain and lift curves, feature importance, learning curves, elbow curves, PCA visualizations, or old `classifier_factory` / `clustering_factory` compatibility code.
This root skill is a router. Read the focused sub-skill for the plotting family you need, then come back here only for install guidance, environment compatibility, or cross-cutting troubleshooting.
## Install and smoke
The public package name is `scikit-plot` and the import name is `scikitplot`.
For PyPI use against this 0.3.7 snapshot:
```bash
python -m pip install "scikit-plot==0.3.7" "scipy<1.11" "matplotlib<3.9"
```
For a local checkout of the package source:
```bash
python -m pip install -e .
```
If you are already in a modern scientific stack and imports or first plots fail, use the compatibility window verified for this repository:
- `scipy<1.11`
- `matplotlib<3.9`
After install, run the root smoke check:
```bash
python scripts/check_environment.py
```
That helper imports the package, prints the version, and runs a tiny Agg-backed confusion-matrix smoke.
## Route map
| User need | Read next |
| --- | --- |
| Confusion matrix, ROC, precision-recall, KS, calibration, cumulative gain, lift, silhouette | `sub-skills/metrics/SKILL.md` |
| Feature importance or learning-curve plots | `sub-skills/estimators/SKILL.md` |
| Elbow curves for clusterers | `sub-skills/clustering/SKILL.md` |
| PCA component variance or 2-D projection | `sub-skills/decomposition/SKILL.md` |
| `classifier_factory`, `clustering_factory`, or deprecated `plotters` usage | `sub-skills/legacy-factories/SKILL.md` |
## What this root owns
- Install and compatibility notes for the 0.3.7 snapshot.
- The package-level smoke check.
- Routing to the five workflow sub-skills.
- Cross-cutting troubleshooting that applies before you know the exact plot family.
## What this root does not own
- Exact API signatures for plot functions.
- Long workflows or examples.
- Legacy method-injection details.
- Sub-skill-specific troubleshooting.
## Read next
- `references/workflow-map.md` for a compact capability map.
- `references/troubleshooting.md` for version-compatibility and import failures.
- `references/repo-provenance.md` to decide whether this skill still matches the checkout.
- `scripts/check_environment.py` to verify the install quickly.
## Fast selection hints
- If the user names a plot family, route by the plot name rather than by the module name.
- If the user says “legacy factory” or “deprecated plotters”, route to `legacy-factories`.
- If the user only wants to know whether the package is installed, the root smoke script is enough.
- If the user is trying to fix a failure, read root troubleshooting first, then the sub-skill troubleshooting page for the plot family.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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