Review code for performance: complexity, database/query efficiency, I/O and network cost, memory and allocation behavior, concurrency contention, caching, and latency/throughput regressions. Cognitive-only atomic skill; output is a findings list.
Quickly install review-performance AI skill to your development environment via command line
Source: nesnilnehc/ai-cortex.
Review code for performance concerns only. Do not define scope (diff vs codebase) or perform security/architecture/language-framework convention analysis; those are handled by other atomic skills. Emit a findings list in the standard format for aggregation. Focus on algorithmic complexity, query efficiency, I/O and network cost, memory behavior, contention and concurrency bottlenecks, caching strategy, and measura...
When to use: When the task includes performance review. Scope and code range are determined by the caller or user.
Edge case: No clear performance risk in small formatting diff
Review code for performance: complexity, database/query efficiency, I/O and network cost, memory and allocation behavior, concurrency contention, caching, and latency/throughput regressions. Cognitive-only atomic skill; output is a findings list. Source: nesnilnehc/ai-cortex.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/nesnilnehc/ai-cortex --skill review-performanceReview code for performance: complexity, database/query efficiency, I/O and network cost, memory and allocation behavior, concurrency contention, caching, and latency/throughput regressions. Cognitive-only atomic skill; output is a findings list. Source: nesnilnehc/ai-cortex.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/nesnilnehc/ai-cortex --skill review-performance Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/nesnilnehc/ai-cortex