Results for “optimize”

Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."

The English summary is being prepared. Showing the original description.

Django performance code review. Use when asked to "review Django performance", "find N+1 queries", "optimize Django", "check queryset performance", "database performance", "Django ORM issues", or audit Django code for performance problems.

The English summary is being prepared. Showing the original description.

Audit and optimize application performance, including bundle size, rendering, database queries, and Core Web Vitals.

The English summary is being prepared. Showing the original description.

High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.

The English summary is being prepared. Showing the original description.

Publication-quality physics plots — vector fields, streamlines, contour maps, 3D surfaces, phase space, spectrograms, and animations. Optimized for journal submission with LaTeX labels, proper colormaps, and multi-panel layouts.

The English summary is being prepared. Showing the original description.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

The English summary is being prepared. Showing the original description.

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.

The English summary is being prepared. Showing the original description.

Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.

The English summary is being prepared. Showing the original description.

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

The English summary is being prepared. Showing the original description.

Orchestrate the full ToolUniverse self-improvement cycle: discover APIs, create tools, test with researcher personas, fix issues, optimize skills, and push via git. References and dispatches to all other devtu skills. Use when asked to: run the self-improvement loop, do a debug/test round, expand tool coverage, improve tool quality, or evolve ToolUniverse.

The English summary is being prepared. Showing the original description.

Diagnose and fix UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

The English summary is being prepared. Showing the original description.

Explain and control the stellar-build learning loop — the system that improves your skills from how you use them. Use when the user says "learning loop", "how does the learning loop work", "what is the learning loop", "self-improving skills", "stellar-loop", "show my skill usage", "is tracing on", or wants an overview / status of the local trace-capture + optimize + bench cycle.

The English summary is being prepared. Showing the original description.

Benchmark stellar-build skills to measure quality and the lift from optimization. Use when the user says "bench my skills", "bench-skills", "benchmark skills", "did optimization help", "measure my skills", "stellar-loop bench", or wants to quantify whether /optimize-skills actually improved things. Held-out eval prompts scored by an LLM judge, reproducible with fixed seeds. Fully local.

The English summary is being prepared. Showing the original description.

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," or "breadcrumb schema." For broader SEO issues, see seo-audit.

The English summary is being prepared. Showing the original description.

When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.

The English summary is being prepared. Showing the original description.

When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.

The English summary is being prepared. Showing the original description.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

The English summary is being prepared. Showing the original description.

Optimize affiliate programs with commission and activation. TRIGGERS - Use when user needs help with affiliate-optimization related tasks.

The English summary is being prepared. Showing the original description.

Optimize accounts payable processes. TRIGGERS - Use when user needs help with accounts-payable-optimization related tasks.

The English summary is being prepared. Showing the original description.

Optimize accounts receivable processes. TRIGGERS - Use when user needs help with accounts-receivable-optimization related tasks.

The English summary is being prepared. Showing the original description.

Prepare a product photo to meet Amazon's main image requirements: pure white background, square format, 2000×2000px, JPEG.

The English summary is being prepared. Showing the original description.

Smart crop a product photo to Etsy's recommended 2000×2000px square format and export as JPEG.

The English summary is being prepared. Showing the original description.

Resize, enhance, and compress a product photo for an e-commerce listing with consistent quality.

The English summary is being prepared. Showing the original description.

Resize a product photo to Shopify's recommended 2048×2048px square format, sharpen, and convert to WebP for fast storefront load times.

The English summary is being prepared. Showing the original description.