Redacta

Pseudonymise medical and clinical documents before they're processed by AI or shared. Redacta replaces patient identifiers with labelled tokens — [PATIENT_NAME_1], [NHS_NUMBER_1], [DATE_OF_BIRTH_1], … — while leaving the clinical meaning intact, and returns a redaction report alongside the cleaned text.

It's an Agent Skill (the open standard used by Claude and other agents), so it drops into Claude Code, the Claude apps, or the API.

How it works

Two layers:

• Patterns (deterministic). A bundled script (scripts/redact_structured.py, Python standard library only, no network) matches fixed-format identifiers: NHS numbers (Modulus-11 validated), UK National Insurance numbers, dates of birth, UK postcodes, phone numbers, emails, and hospital/MRN numbers. US SSN and ZIP codes are also handled.
• Reasoning (judgement). The skill then has the agent handle what patterns can't: patient names (told apart from the clinicians treating them), postal addresses, and identifying ages.

Install

Claude Code

git clone https://github.com/nickjlamb/redacta ~/.claude/skills/redacta

Then invoke it with /redacta, or let it trigger automatically when you ask to redact or de-identify clinical text.

Claude apps / API

Zip the repository folder and upload it as a skill.

Contents

Path	What it is
SKILL.md	The skill — instructions plus metadata
reference.md	Pattern specs, the Modulus-11 algorithm, NI prefix rules, the date-of-birth vs clinical-date rule, token vocabulary, limitations
scripts/redact_structured.py	The deterministic pattern layer
scripts/test_redact_structured.py	Tests for the pattern layer
evaluations.json	Example evaluation scenarios

Run the pattern-layer tests:

python3 scripts/test_redact_structured.py

A note on limits

Redacta is a strong first line of defence, not a guarantee. It won't catch every possible identifier and isn't a substitute for formal data-protection processes. Always review the redaction report before sharing text.

License

MIT-0 (MIT No Attribution). Built by PharmaTools.AI.