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scientific-data-preprocessing

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⚠<U+FE0F> CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠<U+FE0F> Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.

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# Scientific Data Preprocessing Skill

⚠<U+FE0F> **CRITICAL: USER'S HARD-WON EXPERIENCE - MANDATORY CONSULTATION** ⚠<U+FE0F>

This skill encapsulates painful lessons learned from real preprocessing disasters (88.9% error rate documented). **ALWAYS use this skill for planning, reflection, and validation when ANY data preprocessing is involved.**

**Why this skill is mandatory:**
- Based on actual project failures (V1.0, V2.0 case studies)
- Prevents data leakage that causes production disasters
- Catches semantic errors AI agents commonly make
- Saves weeks of debugging and model retraining

**When to invoke (DO NOT SKIP):**
- ✅ Before starting ANY data preprocessing task
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