145-java-refactoring-high-performance
/145-java-refactoring-high-performance
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
- Author
- jabrena ↗
- Repository
- cursor-rules-java ↗
- Licence
- Apache-2.0
- Last repository change
- 13.11.2026
Assessment and security
- Files in this package
- 4
- Scripts
- 0
- HTML comments
- 0
- URLs in SKILL.md
- 0
No signals detected. Repository changed on 13.11.2026, without references to retired models or APIs.
Apache-2.0, otwarta: można używać i zmieniać, z zachowaniem licencji i informacji o zmianach.
What it does and when to use it
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
Original author description
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
How it works
- Constraints
- When to use this skill
- Workflow
- Reference
SKILL.md preview
--- name: 145-java-refactoring-high-performance description: 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 license: Apache-2.0 metadata: author: Juan Antonio Breña Moral version: 0.19.0 --- # 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. 2. **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. 3. **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). 4. **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-memory-allocation.md) - [references/145-refactoring-high-performance-java-cpu.md](references/145-refactoring-high-performance-java-cpu.md) - [references/145-refactoring-high-performance-java-code-syntax.md](references/145-refactoring-high-performance-java-code-syntax.md)
Files in this package (4)
- SKILL.md 4 KB
- references/145-refactoring-high-performance-java-code-syntax.md 20 KB
- references/145-refactoring-high-performance-java-cpu.md 10 KB
- references/145-refactoring-high-performance-java-memory-allocation.md 33 KB
Versions
The database has no other skills named 145-java-refactoring-high-performance.
Database snapshot: 13.11.2026 · package version 4a0f17882261 (SHA-256 digest of the entire package)
Downloads in the last 30 days: 0 · ranking
Report a problem with this skill: harmful content, incorrect descriptions or an author’s removal request.
Similar skills
- 100163-java-profiling-refactor
Use when you need to refactor Java code based on trusted profiling analysis findings — including reviewing repository-owned or maintainer-sanitized docs/profiling-problem-analysis and docs/profiling-solutions files, identifying specific performance bottlenecks, and implementing… - 95performance-optimization
This skill should be used when the user asks to "optimize", "make faster", "speed up", "reduce memory", "improve performance", "reduce latency", "improve throughput", "profile", "benchmark", or mentions "slow code", "too slow", "performance bottleneck", "high memory usage",… - 90dart-optimization
Use when profiling CPU hot paths, optimizing memory allocations, or enforcing static typing performance in Dart. - 95code-optimizer
Analyzes and optimizes code for better performance, memory usage, and efficiency. Use when code is slow, memory-intensive, or inefficient. Supports Python and Java optimization including execution speed improvements, memory reduction, database query optimization, and I/O… - 86code-refactoring
Expert code refactoring and optimization with analysis, improvements, and documentation. Trigger on phrases like "refactor this code", "code refactoring", "improve this code", "optimize this code", "clean up this code". - 100performance-review
Performance optimization analysis: CPU/memory profiling, caching strategies, database query optimization, connection pooling, concurrency patterns, memory leak detection, and throughput improvement. Use when code is slow, memory usage is high, latency needs reduction, or…