How accurate is the categorization?

The skill uses a tiered matching system, starting with user-defined overrides (1.0 confidence) and exact pattern matches before falling back to intelligent inference based on context.

How does the skill handle Danish characters?

It automatically normalizes characters like Ø to OE and Æ to AE during pattern matching to ensure consistency across different bank exports while preserving the original raw text.

Can I add my own custom merchant rules?

Yes, the skill includes a learning mechanism that saves manual corrections to a categorization markdown file, which Claude references in future sessions to improve accuracy.

Which Danish banks are supported?

The skill is bank-agnostic as it processes raw transaction text patterns, making it compatible with exports from Danske Bank, Nordea, Jyske Bank, and others.

Does it recognize MobilePay and Dankort transactions?

Yes, the skill identifies common Danish payment prefixes like 'Dankort-køb', 'MobilePay', and 'PBS' to help determine both the payment type and the appropriate category.

Danish Transaction Categorizer

Name: Danish Transaction Categorizer
Author: peerjakobsen

bypeerjakobsen

•

Productivity & Workflow

Categorizes Danish bank transactions into spending categories using a comprehensive merchant pattern database.

This skill provides Claude with specialized knowledge of the Danish retail landscape to accurately classify bank transactions. It maps raw transaction strings to normalized merchant names and 15 distinct spending categories like Bolig, Dagligvarer, and Transport. By handling Danish-specific character normalization (Ø, Æ, Å), identifying payment types like Dankort or MobilePay, and implementing a learning loop for manual corrections, it transforms messy financial data into structured insights for personal finance management.

Key Features

012 GitHub stars

02Confidence-based scoring system for intelligent transaction classification

03Persistent learning mechanism that saves user corrections to refine future accuracy

04Automated detection of payment methods including Dankort, MobilePay, and PBS

05Extensive merchant pattern database covering major Danish retailers (Netto, DSB, Wolt, etc.)

06Normalization of Danish special characters for consistent cross-bank pattern matching

Use Cases

01Normalizing raw transaction data for financial dashboards and accounting apps

02Identifying recurring subscription costs and hidden spending patterns in Danish accounts

03Automating personal expense tracking from exported Danish bank CSV files

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add peerjakobsen/smartspender categorization

For use in Claude.ai and ChatGPT

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