Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Communication & Collaboration
Medical Entity Extractor
Extract medical entities (symptoms, medications, lab values, diagnoses) from patient messages.
skill openclawclawhub Free
Extract medical entities (symptoms, medications, lab values, diagnoses) from patient messages.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- 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.
New install
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
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.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- binubmuse
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Medical Entity Extractor
Extract structured medical information from unstructured patient messages.
What This Skill Does
Symptom Extraction: Identifies symptoms, severity, duration, and progression Medication Extraction: Finds medication names, dosages, frequencies, and side effects Lab Value Extraction: Parses lab results, vital signs, and measurements Diagnosis Extraction: Identifies mentioned diagnoses and conditions Temporal Extraction: Captures when symptoms started, how long they've lasted Action Items: Identifies requested actions (appointments, refills, questions)
Input Format
[ { "id": "msg-123", "priority_score": 78, "priority_bucket": "P1", "subject": "Medication side effects", "from": "patient@example.com", "date": "2026-02-27T10:30:00Z", "body": "I've been feeling dizzy since starting the new blood pressure medication (Lisinopril 10mg) three days ago. My BP this morning was 145/92." } ]
Output Format
[ { "id": "msg-123", "entities": { "symptoms": [ { "name": "dizziness", "severity": "moderate", "duration": "3 days", "onset": "since starting new medication" } ], "medications": [ { "name": "Lisinopril", "dosage": "10mg", "frequency": null, "context": "new medication" } ], "lab_values": [ { "type": "blood_pressure", "value": "145/92", "unit": "mmHg", "timestamp": "this morning" } ], "diagnoses": [ { "name": "hypertension", "context": "implied by blood pressure medication" } ], "action_items": [ { "type": "medication_review", "reason": "possible side effect (dizziness)" } ] }, "summary": "Patient reports dizziness after starting Lisinopril 10mg 3 days ago. BP elevated at 145/92. Possible medication side effect requiring review." } ]
Symptoms
Name, severity (mild/moderate/severe), duration, onset, progression (improving/stable/worsening)
Medications
Name, dosage, frequency, route, context (new/existing/stopped)
Lab Values
Type (BP, glucose, cholesterol, etc.), value, unit, timestamp, normal range
Diagnoses
Name, context (confirmed/suspected/ruled out)
Vital Signs
Temperature, heart rate, respiratory rate, oxygen saturation, blood pressure
Action Items
Type (appointment, refill, question, callback), urgency, reason
Medical Terminology Handling
The skill recognizes: Common abbreviations (BP, HR, RR, O2 sat, etc.) Brand and generic medication names Lay terms for medical conditions ("sugar" → diabetes, "heart attack" → MI) Temporal expressions ("since yesterday", "for the past week")
Integration
This skill can be invoked via the OpenClaw CLI: openclaw skill run medical-entity-extractor --input '[{"id":"msg-1","priority_score":78,...}]' --json Or programmatically: const result = await execFileAsync('openclaw', [ 'skill', 'run', 'medical-entity-extractor', '--input', JSON.stringify(scoredMessages), '--json' ]); Recommended Model: Claude Sonnet 4.5 (openclaw models set anthropic/claude-sonnet-4-5)
Privacy & Security
All processing happens locally via OpenClaw No data is sent to external services (except Claude API for LLM processing) Extracted entities remain in your local environment
Category context
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md