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Found 1,578 Skills
Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics, kinetics, and analytical techniques (spectroscopy, chromatography, mass spectrometry). Provides insights on chemical processes, material properties, reaction pathways, synthesis, and analytical methods. Use when: Chemical reactions, material analysis, synthesis planning, process optimization, environmental chemistry. Evaluates: Molecular structure, reaction mechanisms, yield, selectivity, safety, environmental impact.
Transforms vague or simple user prompts into high-quality, structured, and high-performance AI instructions using systematic optimization techniques like XML tagging, few-shot examples, and Chain-of-Thought. Use this skill when you need to improve the reliability, accuracy, or formatting of an AI's output.
T-SQL query optimization techniques for SQL Server and Azure SQL Database. Use this skill when: (1) User needs to optimize slow queries, (2) User asks about SARGability or index seeks, (3) User needs help with query hints, (4) User has parameter sniffing issues, (5) User needs to understand execution plans, (6) User asks about statistics and cardinality estimation.
Based on collected materials, we provide high-quality blog post writing (especially technical blogs), SEO optimization, and structure proposals.
Use this skill for Next.js App Router patterns, Server Components, Server Actions, Cache Components, and framework-level optimizations. Covers Next.js 16 breaking changes including async params, proxy.ts migration, Cache Components with "use cache", and React 19.2 integration. For deploying to Cloudflare Workers, use the cloudflare-nextjs skill instead. This skill is deployment-agnostic and works with Vercel, AWS, self-hosted, or any platform. Keywords: Next.js 16, Next.js App Router, Next.js Pages Router, Server Components, React Server Components, Server Actions, Cache Components, use cache, Next.js 16 breaking changes, async params nextjs, proxy.ts migration, React 19.2, Next.js metadata, Next.js SEO, generateMetadata, static generation, dynamic rendering, streaming SSR, Suspense, parallel routes, intercepting routes, route groups, Next.js middleware, Next.js API routes, Route Handlers, revalidatePath, revalidateTag, next/navigation, useSearchParams, turbopack, next.config
Expert helper for Docker containers, Docker Compose, and container optimization
An automated SEO testing tool based on official Google documentation. It automatically analyzes a website's technical SEO, content metadata, performance experience, and link structure, and outputs a test report that aligns with Google's best practices. Use cases: (1) Analyze website SEO status, (2) Diagnose search engine ranking issues, (3) Verify if pages comply with Google Search Essentials standards, (4) Generate actionable SEO optimization recommendations.
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
Measure and improve how well your AI works. Use when AI gives wrong answers, accuracy is bad, responses are unreliable, you need to test AI quality, evaluate your AI, write metrics, benchmark performance, optimize prompts, improve results, or systematically make your AI better. Covers DSPy evaluation, metrics, and optimization.
Generate synthetic training data when you don't have enough real examples. Use when you're starting from scratch with no data, need a proof of concept fast, have too few examples for optimization, can't use real customer data for privacy or compliance, need to fill gaps in edge cases, have unbalanced categories, added new categories, or changed your schema. Covers DSPy synthetic data generation, quality filtering, and bootstrapping from zero.
Track which optimization experiment was best. Use when you've run multiple optimization passes, need to compare experiments, want to reproduce past results, need to pick the best prompt configuration, track experiment costs, manage optimization artifacts, decide which optimized program to deploy, or justify your choice to stakeholders. Covers experiment logging, comparison, and promotion to production.
Reduce your AI API bill. Use when AI costs are too high, API calls are too expensive, you want to use cheaper models, optimize token usage, reduce LLM spending, route easy questions to cheap models, or make your AI feature more cost-effective. Covers DSPy cost optimization — cheaper models, smart routing, per-module LMs, fine-tuning, caching, and prompt reduction.