Compare generated Java models against openai-java classes field by field.
npx skills add https://github.com/Azure/azure-sdk-for-java --skill dup-classes
Please help me install this Agent Skill. Skill: dup-classes Source: https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/.workflow_docs/dup-classes Command: npx skills add https://github.com/Azure/azure-sdk-for-java --skill dup-classes
This Skill identifies and categorizes duplicate Java model classes generated by the SDK against existing models in the openai-java library, helping to manage code redundancy and ensure accurate model coverage.
openai-java models based on fields and types, even with differing names.Use the dup-classes skill to compare generated Java models in './src/main/java' against the openai-java dependency found in the pom.xml in the current directory.
High-intent search queries and answers about installing and using this skill.
Detecting duplicate Java models involves performing field-by-field comparison of shapes and types against the openai-java library. This identifies actionable duplicates, structural equivalents within type hierarchies, and partial matches to manage code redundancy.
The best way to compare generated Java classes with openai-java models is through field-by-field structural comparison. This method distinguishes between actionable duplicates, structural equivalents within type hierarchies, and partial matches, even when class names differ.
Yes, you can find duplicate Java classes with different names. The duplicate detection mechanism compares generated classes based on their fields and types rather than names, successfully identifying structural equivalents and partial matches for code redundancy management.
Yes, you need a pom.xml to check for duplicate Java models. The comparison requires resolving the openai-java dependency version from a provided pom.xml in the current directory before scanning generated source roots for duplicates.
Your generated SDK has redundant OpenAI data structures because newly generated models for features like chat completions often unnecessarily duplicate existing OpenAI data structures. Comparing these against the openai-java library identifies which duplicates can be safely removed.
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