Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/alkoleft/platform-context-exporterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/alkoleft/platform-context-exporter/133-java-data-oriented-programming)<a href="https://agentmods.dev/rules/alkoleft/platform-context-exporter/133-java-data-oriented-programming"><img src="https://agentmods.dev/badge/rules/alkoleft/platform-context-exporter/133-java-data-oriented-programming/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/alkoleft/platform-context-exporter/133-java-data-oriented-programming"><img src="https://agentmods.dev/badge/rules/alkoleft/platform-context-exporter/133-java-data-oriented-programming.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.07857 | $0.07857 |
| Opus 5.5 | $0.03143 | $0.03143 |
| Sonnet 5.5 | $0.01571 | $0.01571 |
| Haiku 4.5 | $0.00786 | $0.00786 |
Grade A, and why
133-java-data-oriented-programming scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 919 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Java rules to apply data oriented programming style
Java Data-Oriented Programming emphasizes separating code (behavior) from data structures, which should ideally be immutable (e.g., using records). Data manipulation should occur via pure functions that transform data into new instances. It's often beneficial to keep data structures flat and denormalized (using IDs for references) where appropriate, and to start with generic data representations (like Map<String, Object>) converting to specific types only when necessary. Data integrity is ensured through pure validation functions. Flexible, generic data access layers facilitate working with various data types and storage mechanisms. All data transformations should be explicit, traceable, and composed of clear, pure functional steps.
Implementing These Principles
These guidelines are built upon the following core principles:
- Separation of Concerns (Data vs. Code): Strictly decouple data structures (which should be simple carriers like records or POJOs) from the code (behavior) that operates on them. Behavior should reside in separate utility classes or services.
- Immutability: Design data structures to be immutable. Use records or final fields, and ensure that any transformations on data produce new instances rather than modifying existing ones.
- Pure Data Transformations: Manipulate data using pure functions that depend only on their inputs and produce no side effects. This makes transformations predictable, testable, and easier to reason about.
- Simplicity and Flexibility of Data Structures: Prefer flat, denormalized data structures where appropriate, using IDs for references rather than deep nesting. Start with generic representations (like
Map<String, Object>) if the schema is dynamic, converting to specific types only when necessary for processing. - Explicit and Traceable Operations: Ensure all data validation and transformation steps are explicit, composed of clear functional steps, and easily traceable. Avoid hidden or implicit logic within data objects.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 919 lines · 7,857 tokens per session scan A e11a61b343c6
133-java-data-oriented-programming is a cursor rule published in the GitHub repository alkoleft/platform-context-exporter (48 stars, last pushed 1y ago), licensed MIT. It adds 7,857 tokens to every session, about $0.0314 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other cursor rules, from other repositories
1c-extension-patterns
A set of rules and examples for extending 1C configurations with BSL code and XML role metadata. 1C is an enterprise business-application platform, and BSL is its programming language.
testing-patterns
A set of rules and examples for testing 1C code with YaXUnit and Vanessa Automation. YaXUnit is used for unit tests of individual functions, while Vanessa Automation describes user scenarios as “given, when, then” steps.
integrations
A development rule for building 1C integrations with external systems through HTTP APIs. It recommends first making and testing the requests in Python, then translating the working version into 1C’s BSL language.
kotlin
You are a Senior Kotlin programmer with experience in the Android framework and a preference for clean programming and design patterns.
1c-coding-standards
Coding standards for BSL, the programming language used by the 1C business software platform. They cover naming, method documentation, database queries, collections, client-server code, and performance practices.
1c-skd-two-pass-preprocessing
A two-pass method for changing 1C report output before detailed records are combined into grouped totals. 1C's report system, СКД, builds reports by grouping and summarizing data.