ml4t-model-validation skillA
ml4t-model-validation is agent-read markdown (skill) from ml4t/skills: Multi-gate model validation from cross-validation through stress testing to deployment sign-off. Use when qualifying a model for production use..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Model Validation Workflow
A model that passes a single train/test split proves nothing. Rigorous validation requires combinatorial CV, overfitting probability, deflated statistics, feature attribution, and out-of-time holdout - all before any backtest.
## The Problem
A researcher splits data 80/20, trains a model, sees good test-set performance, and runs a backtest. The backtest looks promising. They deploy. The strategy loses money immediately. The cause: the single split was lucky, the model memorized regime-specific patterns, and hyperparameter tuning leaked information across the boundary. Without multiple validation gates, a model that looks good on one split can be arbitrarily overfit.
## The Pattern
### WRONG
```python
# Single train/test split, no overfitting checks, straight to deployment
from sklearn.model_selection import train_test_split
import lightgbm as lgb
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, shuffle=True)
model = lgb.LGBMRegressor().fit(X_train, y_train)
score = model.score(X_test, y_test)
print(f"R2: {score:.3f}") # 0.15 - good enough, deploy
```
### CORRECT
```python
import numpy as np
import lightgbm as lgb
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-model-validation@git:20260901.830d7a8mdr add ml4t/skills/ml4t-model-validation@sha256:1a4e3ab8dd7e09e7Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_6rcincnj2oy5dxrj)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.830d7a8 latest | 2026-09-01 | 830d7a8 | 5,485 B | A | view · diff |
| git:20260901.11976fe | 2026-09-01 | 11976fe | 5,446 B | A | view · diff |
| git:20260901.7d7c020 | 2026-09-01 | 7d7c020 | 5,424 B | A | view · diff |
| git:20260901.297789f | 2026-09-01 | 297789f | 5,423 B | A | view · diff |
| git:20260901.2c5ab85 | 2026-09-01 | 2c5ab85 | 5,361 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 (5485 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 · 19 stars · license Apache-2.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_6rcincnj2oy5dxrj GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-model-validation GET https://markdownregistry.com/api/v1/blob/1a4e3ab8dd7e09e739176093ace141d9db97f7b78865fe3caab958f6b354fc05
Your agent 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.