144-java-data-oriented-programming
Use when you need to apply data-oriented programming best practices in Java — including separating code (behavior) from data structures using records, designing immutable data with pure transformation functions, keeping data flat and denormalized with ID-based references, starting with generic data structures converting to specific types when needed, ensuring data integrity through pure validation functions, and creating flexible generic data access layers. Part of the skills-for-java project
88
85%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
85%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-structured skill description with excellent specificity and completeness. It clearly states when to use it and provides comprehensive detail about the specific practices covered. The main weakness is that trigger terms lean heavily on technical jargon rather than natural language users might employ when seeking help.
Suggestions
Add more natural language trigger terms users might say, such as 'DOP', 'value objects', 'data classes', or 'functional data modeling in Java'
Consider adding simpler trigger phrases like 'how to structure data in Java' or 'Java record patterns' to capture users who may not know the term 'data-oriented programming'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'separating code from data structures using records', 'designing immutable data with pure transformation functions', 'keeping data flat and denormalized with ID-based references', 'starting with generic data structures converting to specific types', 'ensuring data integrity through pure validation functions', and 'creating flexible generic data access layers'. | 3 / 3 |
Completeness | Clearly answers both what (the six specific practices listed) and when ('Use when you need to apply data-oriented programming best practices in Java'). The 'Use when...' clause is explicit at the start of the description. | 3 / 3 |
Trigger Term Quality | Includes relevant technical terms like 'data-oriented programming', 'Java', 'records', 'immutable data', 'pure functions', but these are more technical jargon than natural user language. Missing common variations users might say like 'DOP', 'value objects', or simpler phrases like 'Java data modeling'. | 2 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting 'data-oriented programming' in Java with distinct concepts like records, immutable data, and ID-based references. Unlikely to conflict with general Java skills or other programming paradigm skills due to the specific DOP focus. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill demonstrates strong structure and workflow clarity with appropriate progressive disclosure to a reference file. The constraints section is particularly well-designed with explicit validation checkpoints. The main weakness is the lack of any concrete code examples in the skill itself, requiring users to always consult the reference file for actionable patterns.
Suggestions
Add 1-2 brief code examples showing good vs bad patterns directly in the skill (e.g., a record-based data structure vs a mutable POJO) to make the skill immediately actionable without requiring reference lookup
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is lean and efficient, providing a clear overview without explaining concepts Claude already knows. Every section serves a purpose with no padding or unnecessary context. | 3 / 3 |
Actionability | The skill provides clear constraints and verification commands (mvnw compile, mvn clean verify), but lacks concrete code examples in the main file. It defers all examples to the reference file, making the main skill less immediately actionable. | 2 / 3 |
Workflow Clarity | Clear workflow with explicit validation checkpoints: compile before changes, stop on failure, verify after changes. The MANDATORY/SAFETY/VERIFY structure provides an unambiguous sequence with feedback loops. | 3 / 3 |
Progressive Disclosure | Excellent structure with a concise overview, clear scope definition, and a single well-signaled reference to detailed documentation. One-level-deep reference pattern is properly implemented. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- jabrena/cursor-rules-java
- Commit
7772a1b
- Reviewed
Table of Contents
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