ml-leakage-check skillA
ml-leakage-check is agent-read markdown (skill) from yeaight7/agent-powerups: Use when reviewing ML preprocessing or feature pipelines for target leakage -- validation metrics look suspiciously good, transformers are fitted before splitting, or features may not exist at prediction time..
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
## Purpose Target leakage is the most common and dangerous error in applied ML. It creates models that look perfect in validation but fail instantly in production. This check inspects the pipeline for the standard leakage vectors. ## When to Use - Reviewing preprocessing or feature-engineering code before training sign-off - Validation metrics look too good to be true - A model performed far worse in production than in validation ## Inputs - The preprocessing/feature pipeline code and the train/test split logic ## Workflow 1. **Global scaling/imputation**: was any statistic (mean, std, encoder vocabulary) computed on the *entire* dataset before splitting? That leaks the test distribution into training. 2. **Future features**: is any training feature unavailable at the moment of prediction in real life? (e.g., using "surgery_outcome" to predict "hospital_admission_length") 3. **ID proxies**: are database IDs or row numbers included as features? They often correlate with time or order of entry. 4. **Enforce the order**: Split FIRST, then fit transformers on Train ONLY, then transform Train/Val/Test. ## Output …
Read the whole file at its exact version.
How to install
mdr add yeaight7/agent-powerups/ml-leakage-check@git:20260605.148165emdr add yeaight7/agent-powerups/ml-leakage-check@sha256:20deb9f3b8dbad1fPin 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_wqtiedmwm4uhsi6z)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260605.148165e latest | 2026-06-05 | 148165e | 2,159 B | A | view · diff |
| git:20260502.9f8d76d | 2026-05-02 | 9f8d76d | 988 B | A | view · diff |
| git:20260502.4d09253 | 2026-05-02 | 4d09253 | 137 B | B | 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 (2159 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
yeaight7/agent-powerups · 6 stars · license Apache-2.0 · pushed 2026-09-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_wqtiedmwm4uhsi6z GET https://markdownregistry.com/api/v1/resolve?ref=yeaight7/agent-powerups/ml-leakage-check GET https://markdownregistry.com/api/v1/blob/20deb9f3b8dbad1f38651915f2ec8dc7d4e848ab7a2ed7d87280fce53110c191
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.