Results for “benchmarking”

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

Framework de computação quântica para construir, simular, otimizar e executar circuitos quânticos. Use esta skill ao trabalhar com algoritmos quânticos, design de circuitos quânticos, simulação quântica (com ou sem ruído), execução em hardware quântico (Google, IonQ, AQT, Pasqal), otimização e compilação de circuitos, modelagem e caracterização de ruído, ou experimentos e benchmarking quântico (VQE, QAOA, QPE, randomized benchmarking).

Design and execute performance benchmarks for models and systems. Use when measuring throughput, latency, or comparing system variants.

Guides users through creating, editing, and optimizing agent skills, including drafting, testing, evaluating, and improving skill performance.

Use when evaluating, measuring, or comparing the performance of systems, functions, or services. This skill provides a framework for establishing baselines, measuring performance, and validating that changes meet performance requirements.

Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.

Use when you need to characterize score distributions of a profile HMM on random sequences, such as calibration checks, benchmarking, or filter-behavior experiments.

Measures performance baselines, detects regressions before and after PRs, and compares stack alternatives.

Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.

Measure performance baselines, detect regressions before and after PRs, and compare stack alternatives using browser, API, and build benchmarks.

Guides the creation, modification, and evaluation of agent skills, including running benchmarks and optimizing descriptions for better triggering.

Performance baseline measurement and regression detection. Use when measuring perf before/after a PR, setting up baselines, investigating "feels slow" reports, validating launch performance targets, or comparing your stack against alternatives.

Create, run, configure, and review BenchmarkDotNet microbenchmarks for .NET code, covering project setup, comparison strategies, and cost-aware execution.

Performance regression detection using the browse daemon. (gstack)

Measures application performance first, identifies bottlenecks, and applies targeted fixes for frontend and backend systems.

Performance profiling principles. Measurement, analysis, and optimization techniques.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

Use to compare BPO sites, vendors or partner teams fairly, adjusting for the work mix each is given before concluding anything about performance. Trigger for "compare our BPO sites", "which vendor is performing best", "site A scores lower than site B", outsourcer QBR packs, partner MI reporting, or setting contractual quality targets with a vendor.

Prioritize product work with explicit criteria, scoring, tradeoffs, and decision rationale.

Guides users through creating, refining, and evaluating agent skills, including drafting, testing, and optimizing descriptions for better triggering.

Helps find and analyze competitors to imitate using a five-filter method, focusing on profitability and feasibility while eliminating personal bias.

Use for identifying and resolving performance bottlenecks.

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

Create product objectives, key results, initiatives, guardrails, and review cadence.

Detect brand impersonation attacks across domains, social media, mobile apps, and dark web channels to identify phishing campaigns, fake sites, and unauthorized brand usage.

Delivers measurement-driven performance optimization for latency, throughput, memory, and tail behavior, with correctness preservation and regression guards.

Nocaps: Novel Object Captioning at Scale

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Improve existing content and close the learning loop without cannibalizing new-content work.

Diagnose frame-rate bottlenecks (CPU vs GPU bound FIRST), control Unreal Insights traces, sample live frame times, and annotate performance captures. Use when FPS is low/bad, the game is slow, or you need to find what is limiting the frame rate.