An AI-powered medical report interpreter that recognizes text, highlights abnormal indicators, and provides health advice from local files or image URLs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wisediag-report
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 wisediag-report 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 Medical Report Interpretation (wisediag-report)?
The WiseDiag Medical Report Interpretation skill is a highly specialized integration designed for AI coding agents. It enables agents to parse and interpret complex medical report images—such as blood tests, urine tests, and imaging scans—directly via local binary uploads or public image URLs. By incorporating this capability into your ecosystem of Openclaw Skills, your AI assistant can leverage advanced cloud-based OCR and medical AI models to automatically recognize text, isolate key biological markers, and flag abnormal values.
This tool operates asynchronously, making secure HTTP requests to WiseDiag cloud servers to deliver comprehensive medical insights in Markdown format. As one of the critical health-focused Openclaw Skills, it bridges the gap between raw medical documents and actionable health advice, presenting results directly to users while giving developers a clean command-line interface to orchestrate report interpretation workflows.
WiseDiag Medical Report Interpretation (wisediag-report) Use Cases
- When an end-user uploads a local medical report (e.g., blood test, urine test) and asks "What do these results mean?" or "Help me interpret this report."
- When analyzing medical reports from public URLs instead of local files.
- When your AI agent needs to extract, structure, and highlight abnormal clinical indicator levels from unstructured medical documents.
- When building specialized health-tracking or physical wellness assistants using Openclaw Skills.
How WiseDiag Medical Report Interpretation (wisediag-report) Works
- The user provides a local file path (PDF or image) or a public image URL containing a medical report.
- The AI agent triggers the skill and chooses either
-f/--file(binary stream upload) or--image(remote URL) based on the input type. - The script verifies the
WISEDIAG_API_KEYenvironment variable and constructs an API request. - The medical report data is transmitted securely to the WiseDiag cloud server for OCR text recognition and deep clinical analysis.
- The cloud service returns a stream of diagnostic evaluations, flagging abnormal biomarkers and suggesting logical health advice.
- The tool automatically writes the compiled structured analysis as a Markdown file (
{name}.md) in the current working directory.
WiseDiag Medical Report Interpretation (wisediag-report) Setup
Prerequisites
Ensure you have python3 and pip installed. Next, install the library dependencies:
pip install -r requirements.txt
API Key Configuration
To use WiseDiag Report, you must obtain an API Key from the WiseDiag Console. This key must be set as an environment variable.
export WISEDIAG_API_KEY=your_api_key
Running the Script
There are two mutually exclusive execution methods based on your source data:
Method A: Local File Upload (Recommended)
cd scripts
python3 report.py -f "/path/to/report.jpg"
Method B: Public Image URL
cd scripts
python3 report.py --image "https://example.com/report.jpg"
WiseDiag Medical Report Interpretation (wisediag-report) Data Schema & Taxonomy
The script processes incoming arguments and communicates with the WiseDiag API to build a highly structured patient-facing report. Below is the input parameter schema:
| Parameter | Type | Description | Requirement |
|---|---|---|---|
-f, --file |
Path (String) | Local file path for multipart binary upload. Up to 5 instances allowed. | Mutually exclusive with --image |
--image |
URL (String) | Public HTTP/HTTPS URL of the report image. Up to 5 instances allowed. | Mutually exclusive with -f |
--question |
String | Custom query directing the AI focus (e.g., "Interpret abnormal indicators"). | Optional |
-n, --name |
String | Custom output filename (without extension). | Optional |
-o, --output |
Path (String) | Directory path to save the generated report. | Optional (Defaults to CWD) |
Output Format
All successful processing pipelines automatically output a {name}.md Markdown file. This schema includes:
- OCR Extracted Raw Text: Digital transcription of all text detected in the upload.
- Clinical Indicator Matrix: Tabular representation of recognized biomarkers, reference ranges, and unit measurements.
- Abnormal Levels Alert: Prominent callouts detailing any detected values that sit outside healthy boundaries.
- Refined Health Advice: Plain-English health guidance and dynamic actionable steps (strictly for reference).
WiseDiag Medical Report Interpretation (wisediag-report) Advanced Features
- Multi-File Aggregation: Consolidates up to 5 multi-page report images or distinct files into a single unified analytical report.
- Tailored Inquiry Interface: Supports direct inline patient inquiries via the
--questionprompt parameter to answer contextual medical questions on the fly. - Direct-to-Cloud Stream Processing: Streams local files directly via multipart form data, reducing the need for staging files publicly on external hosts.
- Structured Output Generation: Automatically translates raw medical imagery into beautifully formatted, ready-to-use local markdown reports that integrate cleanly with other Openclaw Skills.
SKILL.md
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