pii-check

Detect PII patterns in crawled data directories and produce redacted outputs.

1|1|Updated Mar 27, 2026
One-click install
npx skills add https://github.com/jadecli/researchers --skill pii-check
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pii-check
Source: https://github.com/jadecli/researchers/tree/main/claude-code-security-review/.claude/skills/pii-check
Command: npx skills add https://github.com/jadecli/researchers --skill pii-check

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Scan extracted and crawled data to identify and flag personally identifiable information to protect privacy and meet compliance standards.

Core Features & Use Cases

  • PII detection: Identify emails, phone numbers, SSNs, API keys, tokens, and other sensitive patterns across text files.
  • Redaction & reporting: Produce redacted outputs and concise audit-ready reports.
  • Use Case: Before sharing crawled data with teams, run scans to surface and redact sensitive data.

Quick Start

Run the detector against a data/ directory to surface PII patterns.

Frequently Asked Questions about pii-check

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify and redact PII in crawled data and text files?

To identify and redact PII in crawled data, run a scanning rule against your data directory to detect emails, phone numbers, SSNs, and API keys. It outputs redacted text files and a confidence score for audit reporting.

What is the best way to scan large datasets for sensitive patterns like API keys and tokens?

Scanning large datasets for sensitive patterns requires applying automated detection rules across directories containing raw data exports. This process flags API keys and tokens, producing a concise redacted output to ensure data privacy before sharing.

Can I detect SSNs and phone numbers in raw data logs for compliance?

Yes, you can detect SSNs and phone numbers in raw data logs by enforcing specific detection rules during the scan. This identifies sensitive patterns across text files to help you meet legal compliance and privacy standards.

Does this PII detection method work with raw data exports and text files?

This PII detection method works directly with directories containing raw data exports, logs, and text files. It applies scalable scans across these datasets to locate sensitive patterns and generate audit-ready reports with confidence scores.

How do I generate audit-ready reports after finding personally identifiable information?

To generate audit-ready reports after finding personally identifiable information, run the detector to produce concise redacted outputs. The scan results include a confidence score for each identified sensitive pattern across your crawled data.

Why should I redact sensitive data before sharing crawled datasets with internal teams?

You should redact sensitive data before sharing crawled datasets to protect privacy and meet compliance standards. Scanning directories surfaces and removes emails, tokens, and SSNs, ensuring teams only receive safe, redacted outputs.