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jabrenajabrena/cursor-rules-java/skills/145-java-refactoring-high-performance/SKILL.md

145-java-refactoring-high-performance

Skill452 starsChanged 3 months agoApache-2.0View on GitHub

Use when you need to refactor Java code for high performance — including memory/allocation reduction, CPU hot-path optimization, and syntax/API/control-flow improvements. This should trigger for requests such as Review Java code for high performance; Optimize Java hot path; Reduce Java allocations; Improve Java latency/throughput. Part of Plinth Toolkit

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    NO PREMATURE OPTIMIZATION: Only optimize code paths identified by profiling evidence

    line 31
  2. Distinctive:

    BEFORE APPLYING: Read the relevant reference(s) for bad/good examples and measurement workflow

    line 32
  3. Distinctive:

    EDGE CASE: If hotspot evidence is unclear, ask clarifying questions before changing code

    line 33

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Java rules for High Performance

Identify and apply practical Java high-performance techniques using a measure-first approach, with emphasis on allocation reduction, data layout, concurrency discipline, and evidence-based validation.

What is covered in this Skill?

  • Measure-first workflow for Java code optimization
  • JVM/runtime-aware coding guidance
  • Allocation reduction techniques with bad/good patterns
  • CPU hot-path simplification and loop-level efficiency patterns
  • Concurrency/backpressure and timeout/cancellation discipline
  • I/O, parsing, and serialization efficiency patterns
  • Persistence/query and caching strategy guidance
  • Java-centric decision workflow: keep/revert based on measured impact

Scope: Practical optimization in application code and APIs. Apply only where profiling indicates real bottlenecks.

Constraints

Performance optimization must be evidence-driven and safe, focused on Java code changes that preserve correctness and maintainability.

  • MEASURE-FIRST: Establish baseline behavior and identify Java code hot paths before optimization
  • NO PREMATURE OPTIMIZATION: Only optimize code paths identified by profiling evidence
  • BEFORE APPLYING: Read the relevant reference(s) for bad/good examples and measurement workflow
  • EDGE CASE: If hotspot evidence is unclear, ask clarifying questions before changing code

When to use this skill

  • Review Java code for high performance
  • Optimize Java hot path
  • Reduce Java allocations
  • Improve Java latency
  • Improve Java throughput

Workflow

  1. Identify Java hotspot and baseline behavior

Confirm the performance-sensitive Java path and baseline behavior before changing code.

  1. Select the relevant reference(s) by bottleneck

Pick and read only the reference(s) matching the observed hotspot: references/145-refactoring-high-performance-java-memory-allocation.md for allocation pressure, primitives vs. wrappers, escape analysis, collection sizing, data layout, and deduplication; references/145-refactoring-high-performance-java-cpu.md for CPU-bound hot paths, bit-level parsing, branchless arithmetic, loop unrolling, Unsafe caution, and SIMD/vectorization; references/145-refactoring-high-performance-java-code-syntax.md for code shape, lambdas, API return conventions, parsing syntax, I/O strategy, concurrency, and control-flow improvements.

  1. Apply targeted optimizations

Implement minimal, evidence-backed changes scoped to the chosen domain(s): memory/allocation, CPU/low-level, or code shape/control flow (and adjacent concurrency, I/O, and persistence/caching in Java code).

  1. Validate and compare code-level outcomes

Compare before/after behavior and keep only Java code changes with meaningful, verified gains.

Reference

For detailed guidance, examples, and constraints, see:

  • references/145-refactoring-high-performance-java-memory-allocation.md
  • references/145-refactoring-high-performance-java-cpu.md
  • references/145-refactoring-high-performance-java-code-syntax.md

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