Analyze and interpret medical checkup reports from PDFs or local files with WiseDiag's advanced AI health analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wiseanalyze
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install wiseanalyze using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is wisediag-checkup?
WiseDiag Checkup is a specialized integration designed to bring medical checkup report analysis to your AI assistants. By leveraging the power of WiseDiag's cloud-based clinical models, this skill transforms raw medical files into structured health interpretations. It helps developers and individuals instantly identify abnormal biological markers, read clinical explanations, and receive personalized lifestyle or wellness advice.
As part of the Openclaw Skills ecosystem, WiseDiag Checkup handles complex medical document analysis seamlessly. It supports multi-format ingestion, allowing users to submit either local file paths or publicly accessible PDF URLs. The output provides high-fidelity, actionable health summaries directly to the conversational agent.
wisediag-checkup Use Cases
- AI agents analyzing patient-provided health report scans and clinical documents.
- Automation pipelines needing to translate raw medical lab PDFs into standard structured formats.
- Virtual healthcare assistants requiring personalized diagnostic interpretations based on medical checkups combined with health questionnaires.
- Users looking to quickly extract actionable insights and abnormal biomarkers from legacy checkup documents.
How wisediag-checkup Works
- Submit File or URL: Initiate the transaction by uploading a local PDF/image (
python3 wise_analyze.py submit -f "/path/to/report.pdf") or submitting a URL (python3 wise_analyze.py submit -u "https://example.com/report.pdf"). - Start Analysis: Spin up the AI processing queue by calling the start sub-command with your unique task ID:
python3 wise_analyze.py start -t "<task_id>". - Dynamic Polling: Query progress using
python3 wise_analyze.py query -t "<task_id>". Adjust polling intervals according to current progress percentage (10 seconds for 0–30%, 8 seconds for 30–70%, and 5 seconds for 70%+). - Download & Present: Download the finished Markdown file using the save sub-command. Present the output verbatim, followed by a concise "关键提醒" (Critical Reminders) containing 2-3 critical points.
wisediag-checkup Setup
Prerequisites and Installation
Ensure you install the required dependencies before running the WiseDiag analyzer:
pip install -r requirements.txt
API Key Configuration
To interact with the WiseDiag cloud infrastructure, obtain your API Key from the WiseDiag Console and configure it as an environment variable:
export WISEDIAG_API_KEY="your_api_key_here"
wisediag-checkup Data Schema & Taxonomy
The skill interacts via structured sub-commands and processes datasets to output a detailed medical summary. Below is the command payload schema:
| Sub-command | Parameters | Description |
|---|---|---|
submit |
-f (file), -u (url), -q (questionnaire), -m (member ID) |
Registers the physical document |
start |
-t (task ID) |
Triggers background inference |
query |
-t (task ID) |
Polls for completion state and progress |
save |
-t (task ID), -n (filename), -o (output dir) |
Outputs finalized report |
Output Data Model
The resulting saved file is a high-quality medical analysis structured as follows:
- Demographics & Analysis Meta: Patient profile details linked via
-m. - Abnormal Metrics Highlight: Clear identification of critical parameters that deviate from standard lab ranges.
- Clinical Interpretations: In-depth explanations of clinical findings.
- Actionable Health Advice: Guidance on lifestyle adjustments, diet, and clinical follow-ups.
- Critical Alerts (关键提醒): The final section detailing the top 2-3 severe items needing immediate attention.
wisediag-checkup Advanced Features
- Dynamic Backoff Polling: Intelligent polling logic dynamically recalibrates API request intervals (10s/8s/5s) based on progress metrics.
- Contextual Questionnaires: Enhance output accuracy by submitting lifestyle or family medical history text with the query.
- Multi-File Aggregation: Run comprehensive consolidated assessments by packaging multiple file types (PDF, JPEG, PNG) into a single submit call.
- Profile Matching Integration: Seamlessly link clinical analyses to ongoing health tracking systems using unique profile member identifiers.
- Local Execution Fallbacks: Includes clear safeguards to prompt user action on highly sensitive, proprietary patient documents.
SKILL.md
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