Common Performance EngineeringSAFE

A collection of Agent Skills Standard and Best Practice for Programming Languages, Frameworks that help our AI Agent follow best practies on frameworks and programming laguages

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: common-performance-engineering
description: Enforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.
metadata:
  triggers:
    files:
    - '**/*.ts'
    - '**/*.tsx'
    - '**/*.go'
    - '**/*.dart'
    - '**/*.java'
    - '**/*.kt'
    - '**/*.swift'
    - '**/*.py'
    keywords:
    - performance
    - optimize
    - profile
    - scalability
    - latency
    - throughput
    - memory leak
    - bottleneck
---
# Performance Engineering Standards

## **Priority: P0 (CRITICAL)**

## Workflow

1. **Baseline**: Profile before changing anything — measure CPU, memory, and latency.
2. **Identify**: Find top bottleneck (N+1 query, hot loop, memory leak).
3. **Fix**: Apply targeted optimization from sections below.
4. **Verify**: Re-profile to confirm improvement and check for regressions.

## Resource Management

- **Memory Efficiency**:
 - Avoid memory leaks: explicit cleanup of listeners, observers, and streams.
 - Optimize data structures: `Set` for lookups, `List` for iteration.
 - Lazy Initialization: Initialize expensive objects only when needed.
- **CPU Optimization**:
 - Aim for O(1) or O(n); avoid O(n^2) in critical paths.
 - Offload heavy computations to background threads or workers.
 - Memoize pure, expensive functions.

See [implementation examples](references/implementation.md) for memoization and batching patterns.

## Network & I/O

- **Payload Reduction**: Use efficient serialization (Protobuf, JSON minification) and compression (gzip/br).
- **Batching**: Group multiple small requests into single bulk operations.
- **Caching**: Implement multi-level caching (Memory -> Storage -> Network) with appropriate TTL and invalidation.
- **Non-blocking I/O**: Always use asynchronous operations for file system and network access.

## UI/UX Performance

- **Minimize Main Thread Work**: Keep animations and interactions fluid by offloading to workers.
- **Virtualization**: Use lazy loading or virtualization for long lists/large datasets.
- **Tree Shaking**: Ensure build tools remove unused code and dependencies.

## Monitoring & Testing

- **Benchmarking**: Write micro-benchmarks for performance-critical functions.
- **SLIs/SLOs**: Define Service Level Indicators (latency, throughput) and Objectives.
- **Load Testing**: Test system behavior under peak and stress conditions.

## Anti-Patterns

- **No premature optimization**: Profile first, fix proven bottlenecks only.
- **No N+1 queries**: Always batch and paginate data-access operations.
- **No synchronous I/O on main thread**: Async all file/network access.

## References

- [Implementation Patterns](references/implementation.md) — profiling patterns, benchmark setup

## Canonical response anchors

When this skill applies, preserve the following domain terminology or equivalent concrete examples in the answer when relevant:
- lazy

- Additional task-grounded exact anchors: premature

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.