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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. This should trigger for requests such as Improve the code with Data-Oriented Programming; Apply Data-Oriented Programming; Refactor the code with Data-Oriented Programming; Model Java data with records and pure functions; Separate Java behavior from immutable data structures; Validate data integrity with pure Java functions. Part of Plinth Toolkit

69

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

70%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is well-organized with a strong validation-gated workflow and good progressive disclosure via a single real reference. Its main weakness is actionability, since the actual refactoring guidance is delegated to the reference rather than shown inline, plus minor redundancy between the intro, 'What is covered', and 'When to use' sections.

Suggestions

Add one or two short inline before/after code snippets (e.g., a POJO vs. an equivalent record with a pure transformation function) so the core refactoring step is actionable without opening the reference.

Remove the redundancy between the intro paragraph, the 'What is covered' bullet list, and the 'When to use' section — consolidate so each idea appears once.

Tie the 'When to use' list to the workflow rather than restating the description's triggers, keeping the body focused on how to execute.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence, but the 'What is covered' bullet list repeats the intro paragraph and the 'When to use' section duplicates trigger phrases already in the description, so not every token earns its place. It is mostly efficient but could be tightened, matching the 'mostly efficient but includes some unnecessary explanation' anchor.

2 / 3

Actionability

Provides concrete executable commands ('./mvnw compile', 'mvn clean verify') and a real reference path, but the core refactor step is abstract ('Implement selected improvements using records, pure transformation functions, flat structures, and explicit validation') with no inline code examples, fitting the 'some concrete guidance but incomplete' anchor rather than fully executable copy-paste guidance.

2 / 3

Workflow Clarity

The four-step workflow has explicit validation checkpoints: compile before changes, 'stop immediately if compilation fails', and verify after, matching the 'clear sequence with explicit validation steps' anchor.

3 / 3

Progressive Disclosure

The body is a concise overview that points to a single one-level-deep, clearly signaled reference (references/144-java-data-oriented-programming.md, a verified real 43KB file), matching the 'clear overview with well-signaled one-level-deep references' anchor.

3 / 3

Total

10

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is comprehensive and well-structured, clearly stating concrete capabilities and providing explicit natural-language triggers for when to use the skill. It is distinctive and unlikely to conflict with other skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions 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', and 'ensuring data integrity through pure validation functions', matching the 'Lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both what (the enumerated capabilities) and when via 'This should trigger for requests such as...', satisfying the explicit-trigger anchor; not capped at 2 because the 'Use when...' trigger guidance is present.

3 / 3

Trigger Term Quality

Provides natural phrasings a user would actually say such as 'Improve the code with Data-Oriented Programming', 'Apply Data-Oriented Programming', and 'Refactor the code with Data-Oriented Programming', giving good coverage of common variations.

3 / 3

Distinctiveness Conflict Risk

Targets a clear niche (Data-Oriented Programming in Java) with distinct triggers and is namespaced as 'Part of Plinth Toolkit', making it unlikely to fire for unrelated skills.

3 / 3

Total

12

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
jabrena/plinth
Reviewed

Table of Contents

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