ml4t-shap-analysis SKILL.md skillA
ml4t-shap-analysis from ml4t/skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add ml4t/skills/ml4t-shap-analysis@git:20260901.c415df0Pins git:20260901.c415df0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- ml4t/skills
- Path
validation/shap-analysis/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260901.c415df0, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 4,853 bytes
- Repository stars
- 41
- License
- Apache-2.0
Explain model predictions with SHAP values instead of biased built-in feature importance. Use when interpreting which features drive model decisions.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# SHAP Analysis
Built-in `feature_importances_` in tree models is biased toward high-cardinality and correlated features. SHAP values provide additive, consistent feature attributions grounded in game theory.
## The Problem
LightGBM's `feature_importances_` (gain or split-based) systematically overweights features with more unique values and features that are correlated with other predictors. Two features with identical predictive power but different cardinality will show different importance. This leads to incorrect feature selection, misleading model narratives, and poor decisions about which signals to keep or discard. SHAP values are the only feature attribution method that satisfies both local accuracy (attributions sum to prediction) and consistency (a feature that contributes more never gets lower attribution).
## The Pattern
### WRONG
```python
import lightgbm as lgb
model = lgb.LGBMRegressor().fit(X_train, y_train)
# Built-in importance - biased toward high-cardinality features
importance = model.feature_importances_
for name, imp in sorted(zip(feature_names, importance), key=lambda x: -x[1])[:5]:
print(f"{name}: {imp}")
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-shap-analysis@sha256:232857d846d3da9dThe line at the top of this page pins the label git:20260901.c415df0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_kfoxgkpp2dtyqk7b)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between May 28, 2026 and Sep 1, 2026, about one every 96 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.c415df0 latest | 2026-09-01 | c415df0 | 4,853 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,865 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4853 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ml4t/skills · 41 stars · license Apache-2.0 · pushed 2026-11-08 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_kfoxgkpp2dtyqk7b GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-shap-analysis GET https://markdownregistry.com/api/v1/blob/232857d846d3da9d814b54d9486f97f6ba0f871276b0100c175beca3782cf571
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.