Results for “bench”

Structured deep research workflow with human-in-the-loop control. Use /research to generate research outline, /research-deep for parallel web search across items, /research-report to compile markdown reports. Supports academic research, benchmark research, technology selection, market analysis, and due diligence. Triggers: 'deep research', 'research topic', 'benchmark comparison', 'technology survey', 'market analysis'. Requires: WebSearch capability.

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).

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.

Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Use the model-recommender skill, Workflow C (Roster Refresh), to research and update the model roster from live benchmarks.

Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

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

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

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

Proposal research workflow that matches local case studies and gathers web evidence into an HTML research dossier. Use when the user needs proposal research, client intel, tech stack discovery, pricing benchmarks, competitive context, or case-study matching for a brief. Triggers: 'research this proposal', 'build a research dossier', 'match case studies', 'find pricing benchmarks', 'client intel for', 'what tech does X use'.

AIDE file integrity monitoring reference. Database initialization, integrity checks, update workflow, aide.conf configuration, selection rules, report parsing, and production deployment with CIS benchmark compliance.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Researching competitors and shaping positioning: feature matrices, SWOT, benchmarking, positioning maps, battle cards, win/loss, LLM brand visibility. Research only — use for strategy, not code.

Design and implement evaluation harnesses for models, agents, and code. Use when creating benchmarks, designing eval metrics, or comparing system outputs.

POLAR v2.0 — ETH Alpha Hunter. The patience benchmark. Thesis exit permanently removed. Scanner enters, DSL exits. +19.8% ROE trades after removing thesis exit.

Run evaluation tasks against a NeMo Platform server using the Evaluator plugin CLI and Python SDK.

Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance using the ax CLI.

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

Compares coding agents head-to-head on reproducible tasks, measuring pass rate, cost, time, and consistency.

Write idiomatic Elixir code with OTP patterns, supervision trees, and Phoenix LiveView. Masters concurrency, fault tolerance, and distributed systems.

Build, deploy, and manage continuous AI agents using a visual workflow editor or development toolkit.

Launches long-running evaluation batches in isolated tmux sessions with pre-flight verification, monitoring, and post-flight analysis for unattended runs.

Framework de otimização multi-objetivo. NSGA-II, NSGA-III, MOEA/D, frentes de Pareto, tratamento de restrições, benchmarks (ZDT, DTLZ), para problemas de design e otimização em engenharia.

Therapeutics Data Commons. Conjuntos de dados prontos para IA em descoberta de drogas (ADME, toxicidade, DTI), benchmarks, divisões de scaffold, oráculos moleculares, para ML terapêutico e predição farmacológica.

Analyzes email sequence performance metrics. Evaluates open rates, click rates, reply rates, and conversion by step. Identifies drop-off points, benchmarks against industry averages, and recommends optimizations.

Design, optimize, and communicate SaaS pricing — tier structure, value metrics, pricing pages, and price increase strategy.

Compare coding agents head-to-head on reproducible tasks with pass rate, cost, time, and consistency metrics.

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