# Send Redacta to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "redacta", "name": "Redacta", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/nickjlamb/redacta", "canonicalUrl": "https://clawhub.ai/nickjlamb/redacta", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/redacta", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=redacta", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "redacta", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-03T10:33:07.940Z", "expiresAt": "2026-05-10T10:33:07.940Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=redacta", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=redacta", "contentDisposition": "attachment; filename=\"redacta-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "redacta" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/redacta" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/redacta", "downloadUrl": "https://openagent3.xyz/downloads/redacta", "agentUrl": "https://openagent3.xyz/skills/redacta/agent", "manifestUrl": "https://openagent3.xyz/skills/redacta/agent.json", "briefUrl": "https://openagent3.xyz/skills/redacta/agent.md" } } ``` ## Documentation ### Redacta Redacta pseudonymises medical documents before AI processing. It detects patient identifiers and replaces them with labelled tokens, preserving clinical meaning while protecting privacy. ### How It Works When a user shares medical text, scan it for patient identifiers and replace them with pseudonymised tokens. The output should be clinically readable but contain no real patient data. ### Structured Identifiers (regex-based) Apply these pattern rules automatically: NHS Numbers (UK) Format: 3-3-4 digits (e.g. 943 476 5919) or 10 consecutive digits Replace with: [NHS_NUMBER] Validation: check digit using Modulus 11 algorithm when possible Dates of Birth / Dates Formats: DD/MM/YYYY, DD-MM-YYYY, DD.MM.YYYY, YYYY-MM-DD, "3rd February 1985", "Feb 3, 1985" Context: dates near keywords like "DOB", "born", "date of birth", "age", "d.o.b" Replace with: [DATE_OF_BIRTH] (when contextually a DOB) or [DATE] (other dates) Preserve clinical dates when clearly not patient-identifying (e.g. "appointment on 15 March") UK Postcodes Format: A9 9AA, A99 9AA, A9A 9AA, AA9 9AA, AA99 9AA, AA9A 9AA Replace with: [POSTCODE] Phone Numbers UK formats: 07xxx, 01xxx, 02xxx, +44 US formats: (xxx) xxx-xxxx, xxx-xxx-xxxx, +1 Replace with: [PHONE_NUMBER] Email Addresses Standard email pattern Replace with: [EMAIL] Hospital / MRN Numbers Context: numbers near "hospital number", "MRN", "patient ID", "unit number", "case number" Replace with: [HOSPITAL_NUMBER] UK National Insurance Numbers Format: 2 letters + 6 digits + 1 letter (e.g. AB123456C) Replace with: [NI_NUMBER] ### Contextual Identifiers (agent reasoning) Use your understanding of clinical documents to detect: Patient Names Look for names in: salutations ("Dear Mrs Jones"), headers ("Patient: John Smith"), references in body text Distinguish patient names from clinician names — do NOT redact doctor/nurse/consultant names unless explicitly asked Replace with: [PATIENT_NAME] If multiple patients mentioned, use: [PATIENT_NAME_1], [PATIENT_NAME_2] Patient Addresses Full or partial addresses (house number + street, or referenced near "address", "lives at", "resides") Replace with: [ADDRESS] Postcodes are handled separately above Ages Specific ages that could identify when combined with other data: "82-year-old", "aged 47" Replace with: [AGE] Context matters: "children aged 5-12" (general) vs "a 73-year-old woman" (specific patient) ### Output Format Return two sections: ### 1. Pseudonymised Document The full document with all identifiers replaced by tokens. Preserve all formatting, paragraph breaks, and clinical content. ### 2. Redaction Report A summary of what was found and replaced: Redaction Report ================ Items pseudonymised: 7 - [NHS_NUMBER] × 1 (line 3) - [PATIENT_NAME] × 2 (lines 1, 5) - [DATE_OF_BIRTH] × 1 (line 2) - [POSTCODE] × 1 (line 8) - [PHONE_NUMBER] × 1 (line 9) - [AGE] × 1 (line 4) Clinical content preserved: ✓ Clinician names preserved: Dr. Sarah Chen, Mr. James Wright ### Rules Never output the original patient identifiers in your response — only the pseudonymised version Preserve all clinical content — medications, diagnoses, procedures, test results, clinical observations Preserve clinician names by default — only redact if the user explicitly asks Preserve hospital/practice names by default — these are institutional, not patient data When uncertain, err on the side of redacting — false positives are safer than false negatives Dates: appointment dates, procedure dates, and follow-up dates should be preserved unless they could identify the patient (e.g. a specific date of birth) Consistency: the same identifier should get the same token throughout the document (e.g. every instance of the patient's name becomes [PATIENT_NAME]) ### Example Input: Dear Mrs Patricia Hartley, DOB: 14/03/1952 (age 73) NHS Number: 943 476 5919 Hospital Number: RXH-2847561 I am writing to inform you of the results of your recent investigations. Mrs Hartley attended the cardiology outpatient clinic on 10 February 2026 under the care of Dr Sarah Chen. Address: 14 Oakfield Road, Headingley, Leeds LS6 3PJ Tel: 0113 278 4532 Output: Dear [PATIENT_NAME], DOB: [DATE_OF_BIRTH] (age [AGE]) NHS Number: [NHS_NUMBER] Hospital Number: [HOSPITAL_NUMBER] I am writing to inform you of the results of your recent investigations. [PATIENT_NAME] attended the cardiology outpatient clinic on 10 February 2026 under the care of Dr Sarah Chen. Address: [ADDRESS], [POSTCODE] Tel: [PHONE_NUMBER] ### What This Skill Does NOT Do Store or transmit patient data Guarantee 100% detection (always review output) Replace formal data protection processes Provide legal compliance certification Process images or PDFs (text input only in v1) ### Privacy Note This skill processes text locally within your AI agent session. No patient data is sent to external services. However, the text is processed by the underlying language model — ensure your model provider's data handling meets your organisation's requirements. Built by PharmaTools.AI — applied AI for pharma and healthcare. ## Trust - Source: tencent - Verification: Indexed source record - Publisher: nickjlamb - Version: 1.0.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-03T10:33:07.940Z - Expires at: 2026-05-10T10:33:07.940Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/redacta) - [Send to Agent page](https://openagent3.xyz/skills/redacta/agent) - [JSON manifest](https://openagent3.xyz/skills/redacta/agent.json) - [Markdown brief](https://openagent3.xyz/skills/redacta/agent.md) - [Download page](https://openagent3.xyz/downloads/redacta)