ml4t-walk-forward-cv SKILL.md skillA
ml4t-walk-forward-cv 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-walk-forward-cv@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/walk-forward-cv/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260901.c415df0, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 4,387 bytes
- Repository stars
- 41
- License
- Apache-2.0
Rolling or expanding window CV that preserves temporal order. Use when evaluating ML models on time-series data where standard k-fold causes temporal leakage.
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
# Walk-Forward Cross-Validation
A single train/test split tells you nothing about how a model adapts over time. Walk-forward CV slides a window through the data, training and testing sequentially, revealing how performance evolves across market regimes.
## The Problem
A single 80/20 train/test split produces one score from one market period. The model may excel in bull markets but fail in drawdowns - you cannot tell. Standard k-fold shuffles time, leaking future data. You need sequential evaluation that mirrors live deployment: train on the past, predict the future, advance, repeat. This exposes regime sensitivity and stationarity failures.
## The Pattern
### WRONG
```python
from sklearn.model_selection import train_test_split
# Single split - one market regime, no adaptation signal
X_train, X_test, y_train, y_test = train_test_split(
X, y, test_size=0.2, shuffle=True # Shuffling leaks future
)
model.fit(X_train, y_train)
print(f"Score: {model.score(X_test, y_test):.3f}") # One number
```
### CORRECT
```python
import numpy as np
from sklearn.model_selection import TimeSeriesSplit
# Walk-forward with gap for label horizon
n_splits = 5
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-walk-forward-cv@sha256:230a9d26991b4bcfThe 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_ljsext264xbfhttw)
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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 | 4,387 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,397 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 (4387 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_ljsext264xbfhttw GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-walk-forward-cv GET https://markdownregistry.com/api/v1/blob/230a9d26991b4bcf4d3694e02942c5e997ad023783a07b56a956986d1290756c
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.