feature-engineering SKILL.md skillA
feature-engineering from qa-aman/claude-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add qa-aman/claude-skills/feature-engineering@git:20260303.8412b01Pins git:20260303.8412b01 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- qa-aman/claude-skills
- Path
skills/by-role/data-scientist/feature-engineering/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260303.8412b01, committed Mar 3, 2026
- Size
- 7,935 bytes
- Repository stars
- 21
- License
- MIT
Design and implement features from raw data for machine learning models. Use when the user says "engineer features", "feature engineering for X", "create features from this dataset", "transform these variables", "encode categoricals", "handle skew", "create interaction features", "lag features", "extract features from text or dates", "improve model performance with better features", or wants to move from raw columns to model-ready inputs.
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
## Overview Based on **"Feature Engineering for Machine Learning"** by Alice Zheng and Amanda Casari. The core principle: features are the interface between raw data and model performance. The right transformation of an existing variable outperforms adding more data or tuning hyperparameters in most real-world settings. Feature engineering is domain knowledge encoded into math - and it is the highest-leverage step in the ML pipeline. ## Workflow ### Step 1: Audit raw columns for engineering opportunity Before transforming anything, catalog what you have and what problems each column has. For each column, note: - Type: numeric continuous, numeric discrete, ordinal categorical, nominal categorical, datetime, text, ID - Problem: skewed, high cardinality, missing, mixed type, free text, leaky (contains target signal from the future) - Engineering opportunity: log transform, binning, encoding, extraction, embedding Create a feature engineering plan as a table before writing any code: ``` | Column | Type | Problem | Planned Transform | |-------------|-----------|------------------|---------------------------| …
Read the whole file at its exact version.
How to install
mdr add qa-aman/claude-skills/feature-engineering@sha256:5b95f93ebcf71445The line at the top of this page pins the label git:20260303.8412b01, 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_lgxvsgv447cfbig3)
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Versions
The registry has recorded 1 version of this file, committed on Mar 3, 2026.
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 (7935 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
qa-aman/claude-skills · 21 stars · license MIT · pushed 2026-10-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_lgxvsgv447cfbig3 GET https://markdownregistry.com/api/v1/resolve?ref=qa-aman/claude-skills/feature-engineering GET https://markdownregistry.com/api/v1/blob/5b95f93ebcf714457c384a6ed1b7bc854191ba36a20dc264bfb11284a829fd07
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.
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