Redacta
Pseudonymises medical and clinical documents by replacing patient identifiers with labelled tokens (e.g. [PATIENT_NAME_1], [NHS_NUMBER_1], [DATE_OF_BIRTH_1]) so the text can be safely processed by AI or shared, with clinical meaning intact. Combines a deterministic pattern layer (NHS numbers with Modulus-11 validation, UK National Insurance numbers, dates of birth, UK postcodes, phone numbers, emails, hospital/MRN numbers) with contextual reasoning for patient names, postal addresses and identifying ages, then returns the redacted document plus a redaction report. Use when the user wants to re
Install
npx skills add nickjlamb/redacta --skill redactagit clone --depth 1 https://github.com/nickjlamb/redacta.git /tmp/redacta
mkdir -p ~/.claude/skills
cp -r /tmp/redacta/. ~/.claude/skills/redactaPersonal skills live in ~/.claude/skills. Use .claude/skills in a project folder to share a skill with your team.
From the SKILL.md
# Redacta Pseudonymise medical text before it is processed by AI or shared: replace patient identifiers with labelled tokens (`[PATIENT_NAME_1]`, `[NHS_NUMBER_1]`, `[DATE_OF_BIRTH_1]`, ...) while leaving the clinical meaning untouched. Return the redacted document plus a redaction report. Redacta works in two layers: - **Layer 1 — patterns (deterministic).** Fixed-format identifiers, matched by a bundled script: NHS numbers (Modulus-11 validated), UK National Insurance numbers, dates of birth, UK postcodes, phone numbers, emails, hospital/MRN numbers. (US SSN and ZIP codes are also handled.) - **Layer 2 — reasoning (your judgement).** Identifiers that do not follow a fixed pattern: patient names, postal addresses and identifying ages. This is where you read context and tell a patient apart from the clinician treating them. ## Workflow Copy this checklist and tick items off as you go: ``` Redaction progress: - [ ] 1. Save the source text to a file - [ ] 2. Run the pattern layer (scripts/redact_structured.py) - [ ] 3. Apply the reasoning layer (names, addresses, ages) - [ ] 4. Assemble the pseudonymised document (formatting preserved) - [ ] 5. Self-check the output for residual identifiers - [ ] 6. Write the redaction report - [ ] 7. Add the limits note ``` ### 1–2. Pattern layer Write the user's text **verbatim** to a temp file, then run the script (execute it — do not read it into context):
Details
- Skill name
redacta- Repository
- nickjlamb/redacta
- License
- MIT-0
- Repo updated
- 6 October 2026
FAQ
What does the Redacta skill do?
Pseudonymises medical and clinical documents by replacing patient identifiers with labelled tokens (e.g. [PATIENT_NAME_1], [NHS_NUMBER_1], [DATE_OF_BIRTH_1]) so the text can be safely processed by AI or shared, with clinical meaning intact. Combines a deterministic pattern layer (NHS numbers with Modulus-11 validation, UK National Insurance numbers, dates of birth, UK postcodes, phone numbers, emails, hospital/MRN numbers) with contextual reasoning for patient names, postal addresses and identifying ages, then returns the redacted document plus a redaction report. Use when the user wants to re
How do I install the Redacta skill?
skills CLI (Claude Code, Cursor, Codex and more): npx skills add nickjlamb/redacta --skill redacta. Skills go in ~/.claude/skills (personal) or .claude/skills (project), and Claude loads them automatically when a task matches the description.
Is Redacta popular?
It lives in nickjlamb/redacta, which has 8 GitHub stars and 0 forks.
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