ml4t-case-study-pipeline skillA
ml4t-case-study-pipeline is agent-read markdown (skill) from ml4t/skills: Filesystem and artifact-contract pattern for reproducible case studies. Use when organizing a research project for reproducibility and collaboration..
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
# Case Study Artifact Pipeline
Ad-hoc notebooks that load data, compute features, train models, and backtest in one file are impossible to debug, reproduce, or extend. This skill is about artifact boundaries and rerun rules, not about whether the research thesis is good.
## The Problem
A quant writes a 500-line notebook that downloads data, engineers features, trains a model, and runs a backtest. It works once. Then: the data source changes, a feature is added, the model is retrained with different parameters, and the backtest uses stale predictions from the old model. Nobody can tell which outputs correspond to which inputs. The notebook becomes untouchable - too risky to change, too opaque to trust.
## The Pattern
### WRONG
```python
# Monolithic notebook - everything in one file, no artifact boundaries
import polars as pl
from sklearn.linear_model import Ridge
prices = pl.read_parquet("prices.parquet")
prices = prices.with_columns(
fwd_ret=pl.col("close").pct_change(21).shift(-21).over("symbol"),
momentum=pl.col("close").pct_change(63).over("symbol"),
volatility=pl.col("close").pct_change().rolling_std(21).over("symbol"),
)
prices = prices.drop_nulls()
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-case-study-pipeline@git:20260901.c415df0mdr add ml4t/skills/ml4t-case-study-pipeline@sha256:fcac2876c9db88b4Pin 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_cbax3csiltkogrow)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.c415df0 latest | 2026-09-01 | c415df0 | 5,919 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 5,931 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 (5919 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_cbax3csiltkogrow GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-case-study-pipeline GET https://markdownregistry.com/api/v1/blob/fcac2876c9db88b4212ef0aee271ec4700c0c9fa47be8db620a52f9be0664227
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.