What problem does it solve? When you receive a structured data export (platform takeout, GDPR export, API dump) containing many CSV files, it is hard to know what the data actually contains before diving into content analysis. This Skill extracts everything the metadata alone can tell you: schemas, timestamps, shared keys, baseline metrics, PII columns, and data gaps. ## Core Features & Use Cases - Schema Mapping & Key Discovery: Extract headers from every CSV, infer column types, and find shared columns that serve as join keys across files. - Temporal Reconstruction: Build an activity timeline from timestamps scattered across files and calculate account lifespan, activity rates, and content creation ratios. - PII Scanning & Gap Analysis: Flag columns containing IPs, emails, or phone numbers, and identify empty files, schema mismatches, and orphan references. - Use Case: You receive a Reddit GDPR export with 20 CSV files. Use this Skill to produce a forensic report covering file inventory, temporal bounds, baseline metrics, and data quality issues before any content-level analysis. ## Quick Start Use the csv-metadata-forensic skill to analyze all CSV files in this export directory and write a forensic reconstruction report to docs/analysis/01-csv-metadata-forensic.md.
