Json Data VisualizerSAFE

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The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: json-data-visualizer
description: "Guide to JSON Crack for visualizing complex JSON data structures"
metadata:
  openclaw:
    emoji: "🌳"
    category: "tools"
    subcategory: "diagram"
    keywords: ["JSON visualization", "data structure diagram", "tree visualization", "API response viewer", "schema explorer"]
    source: "https://github.com/AykutSarac/jsoncrack.com"
---

# JSON Crack Data Visualizer Guide

## Overview

JSON Crack (formerly JSON Visio) is an open-source data visualization tool with over 43K stars on GitHub that transforms JSON, YAML, XML, TOML, and CSV data into interactive graph diagrams. Instead of reading raw nested data structures, researchers can instantly see the hierarchical relationships, nested objects, and array structures as a navigable node-link diagram rendered on an infinite canvas.

For academic researchers, JSON Crack is particularly valuable when working with complex API responses, configuration files, experimental metadata schemas, and nested data exports. Bioinformatics researchers dealing with deeply nested gene ontology JSON files, social scientists working with survey platform API responses, and computational researchers inspecting machine learning model configuration files all benefit from being able to see their data structures visually rather than scrolling through thousands of lines of text.

The tool is available as a hosted web application at jsoncrack.com, as a self-hosted Docker deployment for institutional use, and as an embeddable React component that can be integrated into custom research tools. It also provides an API for programmatic access, making it suitable for integration into data processing pipelines.

## Getting Started

### Web Application Usage

The fastest way to use JSON Crack is through the web interface. Paste or upload JSON data and the visualization renders immediately.

### Self-Hosted Deployment for Research Labs

```bash
# Clone the repository
git clone https://github.com/AykutSarac/jsoncrack.com.git
cd jsoncrack.com

# Install dependencies
npm install

# Start development server
npm run dev

# Or build and serve for production
npm run build
npm start
```

### Docker Deployment

```bash
# Run with Docker
docker run -d -p 8888:8080 \
  --name json-crack \
  --restart unless-stopped \
  jsoncrack/jsoncrack

# Access at http://localhost:8888
```

### Docker Compose for Lab Infrastructure

```yaml
version: "3.8"
services:
  json-crack:
    image: jsoncrack/jsoncrack
    container_name: json-crack
    ports:
      - "8888:8080"
    restart: unless-stopped
```

## Visualizing Research Data Structures

### Experimental Metadata Schema

Researchers frequently work with complex nested JSON structures for experimental metadata. JSON Crack makes these immediately readable.

```json
{
  "experiment": {
    "id": "EXP-2026-0142",
    "title": "Effect of Temperature on Protein Folding Kinetics",
    "principal_investigator": {
      "name": "Dr. Jane Smith",
      "orcid": "0000-0002-1234-5678",
      "affiliation": "Department of Biochemistry"
    },
    "protocol": {
      "version": "3.2",
      "steps": [
        {
          "order": 1,
          "name": "Sample Preparation",
          "duration_minutes": 120,
          "equipment": ["centrifuge", "spectrophotometer"],
          "parameters": {
            "temperature_celsius": 25,
            "buffer_ph": 7.4,
            "concentration_mm": 0.5
          }
        },
        {
          "order": 2,
          "name": "Thermal Denaturation",
          "duration_minutes": 180,
          "temperature_range": {
            "start": 25,
            "end": 95,
            "step": 1,
            "unit": "celsius"
          }
        },
        {
          "order": 3,
          "name": "Data Acquisition",
          "instrument": "circular_dichroism_spectrometer",
          "wavelength_range_nm": [190, 260]
        }
      ]
    },
    "samples": [
      {
        "id": "S001",
        "condition": "wild_type",
        "replicates": 3,
        "measurements": {
          "tm_celsius": 68.2,
          "delta_h_kcal": -45.3,
          "r_squared": 0.997
        }
      }
    ]
  }
}
```

When loaded into JSON Crack, this structure displays as an interactive tree diagram where each nested object becomes a card node, arrays show their elements as connected child nodes, and researchers can click to expand or collapse sections for focused exploration.

### API Response Inspection

When working with research APIs (PubMed, CrossRef, OpenAlex, etc.), responses are often deeply nested. JSON Crack helps researchers understand the response schema before writing parsing code.

```python
import requests
import json

# Fetch metadata from CrossRef API
response = requests.get(
    "https://api.crossref.org/works/10.1038/nature12373"
)
data = response.json()

# Save for visualization in JSON Crack
with open("crossref_response.json", "w") as f:
    json.dump(data, f, indent=2)

# Open crossref_response.json in JSON Crack to explore the schema
# This reveals the nested structure of author arrays, funding info,
# reference lists, and license metadata
```

## Embedding in Research Applications

JSON Crack provides a React component that can be embedded in custom research tools.

### React Component Integration

```tsx
import { JsonCrackEmbed } from "jsoncrack-react";
import { useState } from "react";

function DataSchemaViewer({ experimentData }) {
  const [jsonContent, setJsonContent] = useState(
    JSON.stringify(experimentData, null, 2)
  );

  return (
    <div style={{ width: "100%", height: "600px" }}>
      <h3>Experiment Data Schema</h3>
      <JsonCrackEmbed
        json={jsonContent}
        style={{ width: "100%", height: "100%" }}
      />
    </div>
  );
}
```

### Embedding via iframe

```html
<iframe
  src="https://jsoncrack.internal.lab/widget"
  width="100%"
  height="600"
  style="border: 1px solid #e5e7eb; border-radius: 8px;"
></iframe>
```

## Supported Data Formats

JSON 

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.