Performance Engineering Standards
SkillDocs & knowledgeEnforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Performance Engineering Standards skill
What this skill tells your AI
The instructions your AI receives, as published by hoangnguyen0403/agent-skills-standard in skills/common/common-performance-engineering/SKILL.md and read by ahel’s review.
Priority: P0 (CRITICAL)
Workflow
- Baseline: Profile before changing anything — measure CPU, memory, and latency.
- Identify: Find top bottleneck (N+1 query, hot loop, memory leak).
- Fix: Apply targeted optimization from sections below.
- 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:
Setfor lookups,Listfor 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 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 — 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
Signals
- GitHub stars
- 565
- Forks
- 163
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
common-performance-engineering- Source
- github.com/hoangnguyen0403/agent-skills-standard