ml4t-causal-identification SKILL.md skillA
ml4t-causal-identification 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-causal-identification@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
concepts/causal-identification/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260901.c415df0, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 5,760 bytes
- Repository stars
- 41
- License
- Apache-2.0
Validate causal claims using DAG adjustment sets, bad-control detection, and refutation tests. Use when distinguishing genuine factor effects from confounded associations.
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
# Causal Identification
A factor with IC 0.04 could be a real effect or a confounded association. Without a DAG and refutation tests, you cannot tell which. Conditioning on the wrong variables - mediators, colliders, post-treatment - can create or destroy apparent signal.
## The Problem
"Kitchen sink regression" - conditioning on every available variable - is the default in ML pipelines. But including a collider (e.g., fund flows driven by both momentum and returns) induces spurious correlation (~-0.25 between independent variables). Including a mediator (the channel through which the treatment operates) attenuates the true effect. Including a post-treatment variable introduces bias of unknown sign. The DAG determines which variables are admissible controls.
## The Pattern
### WRONG
```python
import numpy as np
from sklearn.linear_model import Ridge
# Kitchen-sink: include everything as controls
# fund_flow is a COLLIDER (driven by both momentum and returns) - induces bias
X = np.column_stack([momentum, volatility, fund_flow, sector_return])
model = Ridge().fit(X, forward_returns)
print(f"Momentum coeff: {model.coef_[0]:.4f}") # Biased by collider conditioning
```
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-causal-identification@sha256:8f230ce7e691e93aThe 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_6c6cracvlxyddftj)
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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 | 5,760 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 5,801 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 (5760 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_6c6cracvlxyddftj GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-causal-identification GET https://markdownregistry.com/api/v1/blob/8f230ce7e691e93afc9b9643d2efe2cd827841a45f411edfb27e9d22dac02683
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.