​
Why Use Structure JSON?

Transform any type of unstructured business data into clean, organized JSON objects. This powerful tool can:

  • Standardize Data: Convert messy business documents, emails, and reports into consistent JSON formats
  • Extract Information: Pull specific data points into structured objects ready for system integration
  • Create Relationships: Map complex connections between business entities, departments, and data points
  • Automate Parsing: Turn manual data entry and processing into automated structured workflows
  • Enable Integration: Make your data ready for API consumption and cross-system compatibility

Common business problems this solves:

  • Converting legacy documents into structured data
  • Standardizing data from multiple sources
  • Creating API-ready data structures
  • Extracting specific business metrics from reports
  • Organizing unstructured communications into actionable data

​
Content Input Options

You can provide content to structure in two ways:

  1. Direct Text:
/structure-json structure this data: 
[paste your content here]
  1. File Upload:
/structure-json structure the content from this file: 
[file URL or uploaded file]

Supported file types:

  • Text files (.txt)
  • Word documents (.doc, .docx)
  • CSV files (.csv)
  • PDF files (.pdf)
  • JSON files (for restructuring)
  • XML files
  • HTML files

​
Basic Usage

The /structure-json command uses AI to intelligently convert text or file content into JSON. You have two approaches:

  1. Specify Your Structure:
/structure-json convert this sales report using this structure:
{
  "quarter": string,
  "revenue": number,
  "regions": array of objects
}

[your content or file URL]
  1. Let AI Choose Structure:
/structure-json structure this sales report in the most logical way:
[your content or file URL]

​
Business Use Cases

​
1. Sales Report Parser

/structure-json parse this quarterly sales report with breakdowns by region and product line:
[report text or file URL]

Example Output:

{
  "reportMetadata": {
    "quarter": "Q1 2024",
    "generatedDate": "2024-03-15",
    "currency": "USD"
  },
  "summary": {
    "totalRevenue": 2500000,
    "growthFromLastQuarter": 15.3,
    "topPerformingRegion": "APAC"
  },
  "regionalBreakdown": [
    {
      "region": "APAC",
      "revenue": 1200000,
      "topProducts": [
        {
          "name": "Enterprise Suite",
          "revenue": 800000,
          "growth": 22.5
        }
      ],
      "keyMetrics": {
        "customerAcquisition": 145,
        "churnRate": 2.3
      }
    }
  ],
  "productLines": [
    {
      "category": "Enterprise Solutions",
      "totalRevenue": 1800000,
      "products": [
        {
          "name": "Enterprise Suite",
          "revenueContribution": 1200000,
          "margin": 68
        }
      ]
    }
  ]
}

​
2. Customer Feedback Analyzer

/structure-json analyze these customer feedback emails and structure by sentiment, category, and priority:
[feedback content or file URL]

Example Output:

{
  "analysisMetadata": {
    "periodCovered": "March 2024",
    "totalFeedbackCount": 250,
    "processingDate": "2024-03-15"
  },
  "summary": {
    "averageSentiment": 0.65,
    "topIssues": ["performance", "pricing", "ui"],
    "criticalCount": 15
  },
  "categorizedFeedback": [
    {
      "category": "Performance",
      "count": 85,
      "averageSentiment": 0.45,
      "issues": [
        {
          "description": "Dashboard loading time",
          "frequency": 28,
          "priority": "high",
          "impact": "Revenue at risk: $50K",
          "reportedBy": [
            {
              "accountTier": "Enterprise",
              "region": "EMEA",
              "revenueImpact": "high"
            }
          ]
        }
      ]
    }
  ],
  "actionItems": [
    {
      "priority": "high",
      "task": "Dashboard optimization",
      "assignedTeam": "Engineering",
      "deadline": "2024-03-30"
    }
  ]
}

​
3. Contract Information Extractor

/structure-json extract key information from this contract including parties, terms, dates, and obligations:
[contract text or file URL]

Example Output:

{
  "contractDetails": {
    "id": "CTR-2024-0123",
    "type": "Master Service Agreement",
    "effectiveDate": "2024-01-01",
    "expirationDate": "2025-12-31"
  },
  "parties": [
    {
      "role": "Service Provider",
      "name": "Tech Solutions Inc",
      "jurisdiction": "Delaware",
      "representatives": [
        {
          "name": "Sarah Chen",
          "title": "Chief Commercial Officer",
          "contactEmail": "schen@techsolutions.com"
        }
      ]
    }
  ],
  "terms": [
    {
      "category": "Payment",
      "details": "Net 30",
      "conditions": ["Monthly minimum commitment: $50,000"]
    }
  ],
  "obligations": {
    "provider": [
      {
        "requirement": "System uptime",
        "metric": "99.9%",
        "penalty": "10% credit for non-compliance"
      }
    ],
    "client": [
      {
        "requirement": "Payment schedule",
        "metric": "Net 30",
        "penalty": "2% late fee"
      }
    ]
  },
  "compliance": {
    "dataProtection": ["GDPR", "CCPA"],
    "certifications": ["ISO 27001", "SOC 2"]
  }
}

​
4. HR Data Processor

/structure-json structure these employee records with reporting relationships, compensation, and performance metrics:
[employee data or file URL]

Example Output:

{
  "departmentStructure": {
    "name": "Engineering",
    "headcount": 45,
    "budgetUtilization": 0.92,
    "locations": ["SF", "NYC", "London"]
  },
  "employees": [
    {
      "id": "EMP-2024-123",
      "role": {
        "title": "Senior Developer",
        "level": "L5",
        "track": "Technical"
      },
      "compensation": {
        "band": "B4",
        "basePayRange": {
          "min": 150000,
          "max": 180000
        },
        "equityEligible": true
      },
      "performance": {
        "lastReview": "2024-Q1",
        "rating": 4.5,
        "promotionEligible": true,
        "keyAchievements": [
          "Led migration to microservices",
          "Reduced system latency by 40%"
        ]
      },
      "reportingStructure": {
        "reportsTo": "EMP-2024-089",
        "directReports": 3
      }
    }
  ]
}

​
5. File-Specific Examples

​
Excel Report Processing

/structure-json convert this financial spreadsheet into a hierarchical structure with quarterly comparisons:
[Excel file URL]

​
PDF Contract Analysis

/structure-json extract all service level agreements and structure them by service type:
[PDF file URL]

​
Multi-file Integration

/structure-json combine these vendor evaluation forms into a single structured comparison:
[File URL 1]
[File URL 2]

​
Advanced Features

​
1. Custom Schema Mapping

/structure-json map this vendor data to our standard vendor schema:
Schema: [your schema]
Data: [vendor data or file URL]

​
2. Business Entity Relationships

/structure-json identify and map relationships between business units and product lines:
[organizational content or file URL]

​
3. Compliance Data Validation

/structure-json structure this compliance data and validate against regulatory requirements:
[compliance data or file URL]

​
Tips for Success

  1. Clear Instructions

    • Specify business context
    • Indicate critical fields
    • Mention any special handling requirements

Remember: The more specific you are about your business requirements, the better the structured output will match your needs!