Performance review
Configuração global do Cursor: user rules, agent skills, slash commands e hooks com scripts de instalação.
npx -y skills add JoaoAlavarse/cursor-config --skill performance-reviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 15 days oldThe repository was created 15 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Evaluates code, architecture and runtime behavior to identify performance bottlenecks and recommend improvements based on measurable impact. Use when reviewing performance, latency, throughput, or resource usage.
SKILL.md
3.3 KB, as published. Nobody here has run it
Objective
Evaluate the implementation to identify meaningful performance bottlenecks and recommend improvements based on measurable impact.
Prioritize optimizations that provide significant performance benefits without unnecessarily increasing complexity.
Context
Before reviewing:
- If project rules are available, read and follow them.
- Otherwise, infer the project's conventions from the existing codebase.
- Respect the project's architectural and performance-related design decisions.
- Evaluate performance within the application's business, deployment and usage context.
- Do not assume every application requires aggressive optimization.
Review Process
- Understand the application's performance requirements.
- Identify performance-critical code paths.
- Review algorithms, data structures, concurrency and resource usage.
- Evaluate database access, network communication and I/O operations.
- Identify unnecessary allocations, repeated work and inefficient processing.
- Consider scalability under realistic workloads and expected growth.
- Distinguish measured bottlenecks from theoretical optimizations.
- Recommend improvements proportional to their expected impact.
Review Guidelines
Never compromise correctness for performance.
Base conclusions on observable evidence.
Clearly distinguish facts, assumptions and recommendations.
Prioritize measured or observable bottlenecks over theoretical improvements.
Avoid recommending optimizations without a reasonable expectation of measurable benefit.
Do not sacrifice maintainability for insignificant performance gains.
Evaluate trade-offs between performance, readability and complexity.
Consider CPU, memory, disk, network and database performance when relevant.
Prefer improving algorithms and architecture over micro-optimizations.
Evaluate whether caching, batching or parallelism are appropriate rather than assuming they should be introduced.
Avoid recommending additional infrastructure unless justified by the expected performance improvement.
When performance data is unavailable, clearly state the assumptions behind the recommendations.
Avoid recommending premature optimization.
Prefer eliminating unnecessary work over making existing work faster.
Consider whether the performance issue is caused by system design rather than code implementation.
Prefer measuring before optimizing whenever performance metrics or profiling data are available.
Output
Summary
Provide an overall assessment of the application's performance characteristics.
Strengths
Identify effective performance-related design decisions already present.
Findings
Describe each identified performance finding.
For each finding include:
- Description
- Expected Performance Impact
- Evidence
- Recommendation
Risks
Describe potential trade-offs or negative side effects introduced by the recommended optimizations.
Priority
Prioritize the recommendations based on expected performance improvement, implementation effort and complexity.