AI Skill Report Card
Extracting Expense Data
YAML--- name: extracting-expense-data description: Extracts structured expense data from email receipts for expense reporting systems. Use when you have receipt emails that need to be parsed into standardized expense report fields. ---
Quick Start15 / 15
Paste the email content and get structured expense data:
Email: "Your Uber receipt: $24.50 for trip on Oct 15, 2023 from Office Building to Downtown Client Site"
Output:
- Date: 2023-10-15
- Vendor: Uber
- Amount: 24.50
- Category: Ground Transportation
- Description: Trip from Office Building to Downtown Client Site
- Business Purpose: Client meeting travel
Recommendation▾
Add a template or framework section showing the exact output format structure with all possible fields
Workflow15 / 15
- Copy Email Content: Full email text including headers, body, and any structured data
- Parse Key Fields: Extract date, vendor, amount, location/description
- Standardize Format: Convert to consistent date format, decimal amounts
- Categorize: Map to standard expense categories (Meals, Transport, Lodging, etc.)
- Generate Description: Create clear business purpose from context clues
- Validate: Check for missing fields, reasonable amounts, proper formatting
Recommendation▾
Include an example of handling edge cases like foreign currency or missing vendor information
Examples20 / 20
Example 1: Uber Receipt Email Input:
From: Uber <noreply@uber.com>
Subject: Your receipt for trip on October 15
Trip total: $24.50
Date: Sunday, October 15, 2023 at 2:30 PM
From: 123 Business Plaza
To: 456 Client Tower
Output:
Date: 2023-10-15
Time: 14:30
Vendor: Uber
Amount: 24.50
Category: Ground Transportation
Description: Business Plaza to Client Tower
Business Purpose: Client meeting transportation
Example 2: Restaurant Receipt Input:
From: OpenTable <receipts@opentable.com>
Morton's Steakhouse - Your receipt
Date: Oct 20, 2023, 7:15 PM
Subtotal: $89.50
Tax: $7.16
Total: $96.66
Party of 2
Output:
Date: 2023-10-20
Time: 19:15
Vendor: Morton's Steakhouse
Amount: 96.66
Category: Meals & Entertainment
Description: Dinner for 2 people
Business Purpose: Client dinner meeting
Recommendation▾
Consider adding validation criteria or error handling steps for malformed receipt emails
Best Practices
- Look for structured data in email headers and footers
- Parse timestamps into ISO format (YYYY-MM-DD)
- Extract tax/tip breakdowns when present
- Use vendor email domain to identify company names
- Map location data to business purpose context
- Preserve original currency if international
- Flag unusual amounts or categories for review
Common Pitfalls
- Don't assume time zones - check email headers
- Don't miss embedded receipt images with different totals
- Don't ignore itemized breakdowns in favor of summary totals
- Don't auto-categorize without considering context (airport meals vs office meals)
- Don't lose precision on currency conversions
- Don't extract partial data - validate all required fields present