anonymize-doc

PII & Business Data Anonymization

Detect and anonymize PII + sensitive business data using ML-powered detection (Scrubadub + spaCy NER).

Instructions

0. Dependency Check

SKILL_DIR="$(dirname "$(realpath "$0")" 2>/dev/null || echo /home/mat/dev/agent-skills/dstoic/skills/anonymize-doc)"
pip install -q -r "$SKILL_DIR/requirements.txt" && python -m spacy download -q en_core_web_sm 2>/dev/null

1. Ask Mode

Question: "Check for PII/business data (detection only) or anonymize?"

2. Detection

1. Run: python "$SKILL_DIR/scripts/detect.py" <file_path>
2. Parse JSON output → format report (type, line/col, severity, category)
3. Ask: "Proceed with anonymization?"

3. Anonymization

Ask strategy:

Strategy	Use Case	Reversible	GDPR
mask	Max privacy, redaction	No	✅ Full
hash	Analytics, tracking	No	✅ Full
pseudo	Demos, case studies	Yes	⚠️ Partial
token	Financial, vault-backed	Yes	⚠️ Partial
mixed	Complex docs (auto per severity)	Mixed	⚠️ Partial

Run: python "$SKILL_DIR/scripts/anonymize.py" <file_path> --strategy <choice>

Outputs: <file>-anonymized.<ext> + <file>-audit-log.json

4. Safety Rules

• Preserve original file — never overwrite
• Never commit audit logs to git — check .gitignore has *-audit-log.json
• Warn: reversible strategies need secure mapping storage
• GDPR requires irreversible (mask/hash) for full compliance

See reference.md for entity types, severity tiers, compliance details. See examples.md for before/after samples.