Loading...
Loading...
Found 125 Skills
Guides benchmarking and comparing explicit multi-statement transactions versus single-statement CTE transactions in CockroachDB, with fair test methodology, contention analysis, and performance interpretation. Use when comparing transaction formulations, benchmarking CockroachDB workloads under contention, investigating retry pressure, or deciding whether to rewrite multi-step application flows into single SQL statements.
JVM performance tuning - GC optimization, profiling, memory analysis, benchmarking
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
Profile application performance, identify bottlenecks, and optimize hot paths using CPU profiling, flame graphs, and benchmarking. Use when investigating performance issues or optimizing critical code paths.
Detect performance anti-patterns and apply optimization techniques in Go. Covers allocations, string handling, slice/map preallocation, sync.Pool, benchmarking, and profiling with pprof. Use when checking performance, finding slow code, reducing allocations, profiling, or reviewing hot paths. Trigger examples: "check performance", "find slow code", "reduce allocations", "benchmark this", "profile", "optimize Go code". Do NOT use for concurrency correctness (use go-concurrency-review) or general code style (use go-coding-standards).
Create a custom technical indicator using Numba JIT + NumPy. Generates production-grade, O(n) optimized indicator functions with charting and benchmarking.
Use this skill when profiling application performance, debugging memory leaks, optimizing latency, benchmarking code, or reducing resource consumption. Triggers on CPU profiling, memory profiling, flame graphs, garbage collection tuning, load testing, P99 latency, throughput optimization, bundle size reduction, and any task requiring performance analysis or optimization.
High-performance Rust optimization. Profiling, benchmarking, SIMD, memory optimization, and zero-copy techniques. Focuses on measurable improvements with evidence-based optimization.
Run cross-framework agent comparisons using evaluatorq from orqkit — compares any combination of agents (orq.ai, LangGraph, CrewAI, OpenAI Agents SDK, Vercel AI SDK) head-to-head on the same dataset with LLM-as-a-judge scoring. Use when comparing agents, benchmarking, or wanting side-by-side evaluation. Do NOT use when comparing only orq.ai configurations with no external agents (use run-experiment instead).
Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).
This skill should be used when profiling code, optimizing bottlenecks, benchmarking, or when "performance", "profiling", "optimization", or "--perf" are mentioned.