'optimize' 검색 결과

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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."

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill should be used when the user requests social media content creation for Twitter, Instagram, LinkedIn, or Facebook. It generates platform-optimized posts and saves them in an organized folder structure with meaningful filenames based on event details.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

World-class autonomous sales and revenue skill system. Use ANY time the user asks to sell, pitch, prospect, close, negotiate, launch, monetize, build funnels, write outreach, craft proposals, develop pricing, design offers, write sales copy, create email sequences, plan campaigns, position products, handle objections, create playbooks, build pipeline, forecast revenue, develop GTM strategy, optimize conversions, write ad copy, create sales decks, score leads, nurture prospects, upsell, cross-sell, retain customers, write case studies, price products, structure enterprise deals, create battle cards, script discovery calls, build affiliate programs, plan product launches, create webinar funnels, design pricing pages, A/B test offers, analyze unit economics, calculate LTV/CAC, or ANY other sales, revenue, monetization, go-to-market, or commercial growth task. If it involves selling, revenue, deals, pipeline, or commercial strategy — USE THIS SKILL. Trigger aggressively.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Fetch personalized daily horoscope forecasts from zodiac-today.com API based on natal chart calculations. Use when a user wants: (1) daily guidance on what activities to pursue or avoid, (2) life planning help — best days for interviews, travel, romance, important decisions, (3) energy/focus/luck/romance forecasts to optimize their schedule, (4) lucky colors and numbers for the day, (5) future date analysis for planning events, trips, or milestones (paid tiers). Triggers: horoscope, zodiac, star sign forecast, daily guidance, lucky day, best day to, astrology advice, what should I do today, is today a good day for, plan my week astrology. Required env: ZODIAC_API_KEY (hsk_ API key), ZODIAC_PROFILE_ID (birth chart profile ID). Collects sensitive PII (email, birth date, birth city) for natal chart — requires user consent.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete SEO + GEO (Generative Engine Optimization) system for SaaS companies wanting to rank on both Google and AI search engines (ChatGPT, Perplexity, Gemini, Claude). Use this skill whenever the user asks about SEO strategy, keyword research, content planning, writing SEO-optimized articles, auditing their search performance, creating a content calendar, analyzing competitors, or optimizing for AI search visibility. Trigger on: "seo", "keyword research", "content calendar", "rank on google", "search traffic", "write an article", "blog post", "serp", "backlinks", "competitor analysis", "content cluster", "seo audit", "geo optimization", "ai search", "search console", "organic traffic", "content strategy", "publish article", "seo setup", "ranking", "impressions", "ctr", "meta description", "schema markup", "faq schema". Also trigger when a user wants to set up their SaaS blog SEO from scratch, analyze their current rankings, or create a publishing workflow.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

UI/UX design intelligence for web and mobile. Includes 50+ styles, 161 color palettes, 57 font pairings, 161 product types, 99 UX guidelines, and 25 chart types across 10 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, and HTML/CSS). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, and check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, and mobile app. Elements: button, modal, navbar, sidebar, card, table, form, and chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, and flat design. Topics: color systems, accessibility, animation, layout, typography, font pairing, spacing, interaction states, shadow, and gradient.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Compare cross-border e-commerce shipping options, packaging tactics, customs-risk signals, and speed-versus-cost tradeoffs for sellers, operations teams, and marketplace operators. Use when choosing routes, carriers, declaration practices, or packaging plans for parcel shipments without relying on live carrier APIs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AEO — Agent 效果运营平台。自动发现 Agent 效果漂移、诊断根因、运行 AI 数据闭环工具链，给出 AI 效果优化方案。Measure agent performance, attribute outcomes, track quality trends, optimize cost, and monitor SLAs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Maxim social-hook video — engineered for lead gen and top-of-funnel acquisition via 2-Second Hook Science + Zeigarnik + Variable Reward. Platform-optimized short-form that turns scrollers into followers, subscribers, and leads.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create optimized multi-stage Dockerfiles for any language or framework

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Format and draft compelling LinkedIn posts using Unicode bold/italic styling, visual separators, structured sections, and engagement-optimized patterns. USE FOR: draft LinkedIn post, format text for LinkedIn, create social media post, write thought leadership post, convert content to LinkedIn format, LinkedIn carousel text, Unicode bold italic formatting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate a complete MCP server implementation optimized for Copilot Studio integration with proper schema constraints and streamable HTTP support

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create a new specification file for the solution, optimized for Generative AI consumption.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create a formal specification for an existing GitHub Actions CI/CD workflow, optimized for AI consumption and workflow maintenance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create an Architectural Decision Record (ADR) document for AI-optimized decision documentation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Modular orchestration of agent patterns from Anthropic's engineering guide. Intelligently selects and implements prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer, and autonomous agents. Includes pattern combinations and language-specific implementations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.