categorization

Name: categorization
Availability: InStock
Author: peerjakobsen

Classify Danish bank transactions into categories using merchant patterns and normalization rules.

6|Updated Feb 1, 2026

Search Tags:#learning #transactions #normalization #categorization #data-analytics #danish #merchant-patterns

Ready to run

npx skills add https://github.com/peerjakobsen/smartspender --skill categorization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: categorization
Source: https://github.com/peerjakobsen/smartspender/tree/main/skills/categorization
Command: npx skills add https://github.com/peerjakobsen/smartspender --skill categorization

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Danish bank transactions often arrive with inconsistent merchant names and descriptions, making automatic categorization error-prone and time-consuming.

Core Features & Use Cases

Provides Danish merchant knowledge and transaction categorization rules to map raw transactions to standardized categories and merchants.
Normalizes transaction text and applies a structured pattern database to improve accuracy and reduce manual corrections.
Learns from user corrections and updates merchant-overrides and learnings to continuously improve future classifications.

Quick Start

Classify a sample Danish transaction such as "NETTO 1234 København" to the Dagligvarer / Supermarked category.

Frequently Asked Questions about categorization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I categorize Danish bank transactions with inconsistent merchant names?▼

You can categorize Danish bank transactions by applying normalization rules and a structured merchant pattern database to map raw transaction text into standardized categories and subcategories.

Can I automatically classify recurring Danish transactions into expense categories?▼

Yes, automatic categorization supports recurring patterns by leveraging a merchant pattern database and learned user corrections to consistently classify recurring Danish transactions into expense categories.

How does the categorization learning mechanism handle manual corrections?▼

The categorization learning mechanism captures manual user corrections to update merchant overrides and learning rules, continuously improving the accuracy of future transaction classifications.

What's the best way to normalize raw transaction text for Danish banking analytics?▼

The best way to normalize raw transaction text for Danish banking analytics is to apply structured pattern matching against a dedicated merchant database to resolve inconsistencies and map text to categories.

Do I need a specific knowledge base to classify Danish transactions across multiple accounts?▼

Yes, classifying Danish transactions across multiple accounts requires access to a categorization knowledge base, learning rules, and a merchant pattern database to accurately map raw text to categories.

Why does my Danish transaction categorization fail on unrecognized merchant descriptions?▼

Danish transaction categorization fails on unrecognized merchants when raw text does not match existing patterns, requiring user corrections to generate new learning rules and update the merchant pattern database.