Results for “maxim”

Metasuperhypergraph orchestrator with fractal scale-invariant recursion. Activates maximum performance mode through renormalization-group optimization, power-law resource allocation, and homoiconic self-improvement. Triggers on "ultrawork", complex multi-domain tasks, or when parallelization/delegation yields superlinear returns.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.

Optimize machine learning model hyperparameters using grid search, random search, Bayesian optimization, and Hyperband to maximize model performance within a compute budget. Use when the user requests hyperparameter tuning or provides relevant inputs for this workflow.

Optimizes non-signup forms such as lead capture, contact, demo request, application, survey, quote, and checkout forms to maximize completion while preserving data usefulness.

Optimizes non-signup forms such as lead capture, contact, demo request, application, survey, quote, and checkout forms to maximize completion while preserving data usefulness.

Builds accessible, responsive UI components and layouts with shadcn/ui, Tailwind CSS, theming, dark mode, and WCAG 2.1 AA compliance, applying behavioral science principles.

Optimize non-signup forms such as lead capture, contact, demo request, application, survey, quote, and checkout forms to maximize completion while preserving data usefulness.

Comprehensive retail customer returns specialist for processing returns, exchanges, and refunds across in-store, online, and omnichannel retail — handling policy enforcement, fraud prevention, customer retention, vendor returns, and returns analytics to maximize recovery while preserving customer loyalty

Maximize form completion rates for lead capture, contact, demo request, application, survey, quote, and checkout forms by diagnosing friction and applying evidence-based optimizations.

Build and analyze phylogenetic trees using MAFFT, IQ-TREE 2, and FastTree, with visualization via ETE3 or FigTree for evolutionary analysis, microbial genomics, viral phylodynamics, and molecular clock studies.

Guarantee valid JSON, XML, or code structure during text generation using Pydantic models for type-safe outputs, supporting local models (Transformers, vLLM, llama.cpp) and maximizing inference speed with structured generation.

Use this skill when the user asks about team driving — two-driver OTR operations, how teams maximize miles, HOS rules with sleeper berth swap, pay structures, equipment requirements (sleeper berth specs), team retention, and common challenges. Reference 49 CFR 395.1(g).

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.

Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.

Guides dose escalation for obesity pharmacotherapy based on efficacy and tolerability while staying within approved upper dose limits. Triggers include clinician questions like "How should I titrate naltrexone/bupropion if the starting dose is tolerated?" or "What is the maximum liraglutide dose I can use?"

Maximally Endowed Graph Architecture — λ-calculus over bounded n-SuperHyperGraphs with grounded uncertainty, conditional self-duality, and autopoietic refinement. Use when (1) simple graphs insufficient (η<2), (2) multi-scale reasoning required, (3) uncertainty is structured not stochastic, (4) knowledge must self-refactor. Pareto-governed: complexity added only when simpler structures fail validation.

Comprehensive customer success and retention expertise combining onboarding, health scoring, churn prevention, retention strategies, and LTV maximization. Use when designing customer onboarding flows, reducing churn, building health scores, creating retention systems, designing upsells, or improving customer lifetime value. Covers proactive engagement, cancel flows, dunning, re-engagement, and the full customer lifecycle.

Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring, technology, or any capital expenditure. Also use for ROI calculations, IRR, NPV, payback period, build vs buy decisions, lease vs buy analysis, vendor evaluation, or deciding where to allocate limited budget for maximum return.

Expert in Cursor AI IDE - the leading AI-powered code editor. Covers Rules files for project-specific AI behavior, Plan Mode for structured development, Background Agents for parallel work, and advanced features like voice mode and browser integration. Essential for developers maximizing AI-assisted coding productivity. Use when "cursor ai, cursor rules, .cursorrules, cursor composer, cursor agent, plan mode, background agent, cursor tips, cursor, ide, ai-coding, editor, productivity, agent, developer-tools" mentioned.

CEO/founder-mode plan review. Rethink the problem, find the 10-star product, challenge premises, expand scope when it creates a better product. Four modes: SCOPE EXPANSION (dream big), SELECTIVE EXPANSION (hold scope + cherry-pick expansions), HOLD SCOPE (maximum rigor), SCOPE REDUCTION (strip to essentials). Use when asked to "think bigger", "expand scope", "strategy review", "rethink this", or "is this ambitious enough". Proactively suggest when the user is questioning scope or ambition of a plan, or when the plan feels like it could be thinking bigger. (gstack)

Image outpainting on RunComfy via the `runcomfy` CLI — extend a still beyond its original canvas, fill in what the camera didn't capture, change aspect ratio (square → 16:9, portrait → landscape) while preserving the original content. Routes across Nano Banana 2 Edit (default, spatial-language driven), GPT Image 2 Edit (multi-ref with reference-style matching), FLUX Kontext Pro (single-shot maximum-preservation), and the brand edit endpoints (Seedream / Dreamina / Qwen / FLUX 2). Picks the right route based on whether the outpaint is prose-driven, reference-driven, or brand-locked. Triggers on "outpaint", "outpainting", "extend image canvas", "expand the image", "fill in around the photo", "uncrop", "change aspect ratio", "extend frame", "wide-screen from square", or any explicit ask to add canvas around an existing still.

Image outpainting on RunComfy via the `runcomfy` CLI — extend a still beyond its original canvas, fill in what the camera didn't capture, change aspect ratio (square → 16:9, portrait → landscape) while preserving the original content. Routes across Nano Banana 2 Edit (default, spatial-language driven), GPT Image 2 Edit (multi-ref with reference-style matching), FLUX Kontext Pro (single-shot maximum-preservation), and the brand edit endpoints (Seedream / Dreamina / Qwen / FLUX 2). Picks the right route based on whether the outpaint is prose-driven, reference-driven, or brand-locked. Triggers on "outpaint", "outpainting", "extend image canvas", "expand the image", "fill in around the photo", "uncrop", "change aspect ratio", "extend frame", "wide-screen from square", or any explicit ask to add canvas around an existing still.

Image outpainting on RunComfy via the `runcomfy` CLI — extend a still beyond its original canvas, fill in what the camera didn't capture, change aspect ratio (square → 16:9, portrait → landscape) while preserving the original content. Routes across Nano Banana 2 Edit (default, spatial-language driven), GPT Image 2 Edit (multi-ref with reference-style matching), FLUX Kontext Pro (single-shot maximum-preservation), and the brand edit endpoints (Seedream / Dreamina / Qwen / FLUX 2). Picks the right route based on whether the outpaint is prose-driven, reference-driven, or brand-locked. Triggers on "outpaint", "outpainting", "extend image canvas", "expand the image", "fill in around the photo", "uncrop", "change aspect ratio", "extend frame", "wide-screen from square", or any explicit ask to add canvas around an existing still.