Loading...
Loading...
Found 2 Skills
Analyze candidate algorithms for time/space complexity, scalability limits, and resource-budget fit (CPU, memory, I/O, concurrency). Use when feasibility depends on input growth or latency/memory constraints and quantitative bounds are required before implementation; do not use for persistence schema or deployment topology decisions.
Analyzes code for performance and scalability issues, producing fitness scores (1-10) across algorithmic efficiency, database design, caching strategy, scalability readiness, resource utilization, and data pipeline efficiency. Covers services, CLIs, CI scripts, batch jobs, and ML inference code. Use when the user says /review:performance, requests a performance review, asks for scalability analysis, wants to find N+1 queries or Big-O hot paths, asks why something gets slow as data grows, or needs performance fitness scores before shipping. Only reports findings with confidence >= 7/10.