Install
openclaw skills install wiseanalyzeMedical Checkup Report Analysis — Upload a PDF checkup report (via URL or local file binary upload) for AI-powered health interpretation with abnormal item detection, clinical explanations, lifestyle assessment, and personalized recommendations. Supports health questionnaires for tailored analysis. Triggered when the user asks to analyze a checkup report and provides a PDF URL or local file path. Can also be invoked explicitly: say 'Use WiseAnalyze to analyze this checkup report'.
openclaw skills install wiseanalyzeActivate this skill when any of the following conditions are met:
Note: This skill supports both publicly accessible PDF URLs and local file uploads (PDF and images). The most common usage scenario is uploading local files via binary stream (--file), as users typically have report files saved on their device rather than hosted at a public URL.
How to choose (mutually exclusive — pick one):
/home/user/report.pdf, C:\Users\...\report.pdf, or relative path) → use --file (binary upload). This is the primary and most common usage.http:// or https://) → use --url--url and --file together in one commandIMPORTANT - READ BEFORE INSTALLING:
This skill uploads your checkup report to WiseDiag's cloud servers (via PDF URL or direct binary file upload) for AI-powered health analysis.
Do NOT use with sensitive or confidential medical documents unless:
For sensitive documents, use offline/local checkup report analysis tools instead.
An AI-powered medical checkup report analysis tool. Submit a checkup report (via local file upload or publicly accessible PDF URL), and the system will return a structured health interpretation including abnormal items, clinical explanations, lifestyle advice, and personalized recommendations.
The analysis uses an async task model with 4 separate sub-commands. You (the Agent) must call each step and handle polling yourself.
pip install -r requirements.txt
Get your API key: 👉 https://console.wisediag.com/apiKeyManage
The API key MUST be set as an environment variable. The script reads it automatically.
export WISEDIAG_API_KEY=your_api_key
NEVER call any API or HTTP endpoint directly. ONLY use the script sub-commands below.
⚠️ IMPORTANT: Each command makes HTTP requests to an external API and may take 10-30 seconds to complete. Do NOT kill or interrupt a running command — wait for it to finish. The script prints progress messages so you can see it is still working.
The workflow has 4 steps. You MUST follow them in order.
There are two ways to submit — pick one (mutually exclusive):
Option A: Upload local files (recommended) — when user provides local file paths
cd scripts
python3 wise_analyze.py submit -f "/path/to/checkup_report.pdf"
python3 wise_analyze.py submit -f "/path/to/report.pdf" -f "/path/to/scan.jpg"
Option B: Submit via URL — when user provides a public HTTP/HTTPS link
cd scripts
python3 wise_analyze.py submit -u "https://example.com/checkup_report.pdf"
With optional health questionnaire (recommended for better results):
python3 wise_analyze.py submit -f "/path/to/report.pdf" -q "occasional chest tightness, family history of hypertension, poor sleep quality"
With optional member ID to link to a health profile:
python3 wise_analyze.py submit -f "/path/to/report.pdf" -m "HR1017911158367870xxxx"
Output: The script prints TASK_ID=<id>. Save this task ID for the next steps.
How to choose (mutually exclusive — pick one):
/home/user/report.pdf, C:\Users\...\report.pdf) → use -fhttp:// or https://) → use -u-u and -f together in one commandcd scripts
python3 wise_analyze.py start -t "<task_id>"
Output: Prints confirmation that interpretation has started.
⚠️ CRITICAL: You MUST NOT skip this step. Do NOT jump directly to Step 4.
cd scripts
python3 wise_analyze.py query -t "<task_id>"
Output: The script prints machine-readable status:
STATUS=processing
PROGRESS=50
Polling rules:
STATUS=queued or STATUS=processing → tell the user the current progress percentage, then wait and poll again using dynamic intervals based on progress:
PROGRESS 0–30%: wait 10 seconds before next queryPROGRESS 30–70%: wait 8 seconds before next queryPROGRESS 70%+: wait 5 seconds before next querySTATUS=finish → proceed to Step 4STATUS=failed → the task failed, inform the userYou MUST:
finish or failed. Do NOT give up after one check.save command will fail if the task is not finished.cd scripts
python3 wise_analyze.py save -t "<task_id>" -n "report_2025"
Output: The command saves the report and prints REPORT_PATH=<path>.
If -n is not provided, the task ID is used as the filename.
⚠️ IMPORTANT — How to present the result to the user:
After the save command completes, you MUST:
.md file using the path printed in REPORT_PATH=| Flag | Description |
|---|---|
-u, --url | Publicly accessible URL of the PDF checkup report (optional, requires --url or --file) |
-f, --file | Local file path to upload, PDF or image (optional, repeatable for multiple files) |
-q, --questionnaire | Health questionnaire text: symptoms, family history, lifestyle (optional but recommended) |
-m, --member-id | Health profile member ID to link report to existing profile (optional) |
| Flag | Description |
|---|---|
-t, --task-id | Task ID returned from the submit step (required) |
| Flag | Description |
|---|---|
-t, --task-id | Task ID to check status (required) |
| Flag | Description |
|---|---|
-t, --task-id | Task ID to save result (required) |
-n, --name | Output filename stem (default: taskId) |
-o, --output | Output directory (default: current working directory) |
What happens to your files:
--url: The PDF URL is sent to WiseDiag's analysis API, downloaded and processed on their servers--file: Local files are uploaded directly to WiseDiag's servers via multipart/form-dataFor sensitive documents, use offline/local checkup report analysis tools instead.
MIT