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Found 2,421 Skills
Analyze code performance, detect bottlenecks, suggest optimizations for algorithms, queries, and resource usage. Use when improving application performance or investigating slow code.
Expert prompt engineering for creating effective prompts for Claude, GPT, and other LLMs. Use when writing system prompts, user prompts, few-shot examples, or optimizing existing prompts for better performance.
Use this when the user asks about performance, slowness, optimization, or wants to make code more efficient. Focus on hot paths, unnecessary work, and algorithmic complexity.
Odoo 17.0 full-stack development skill for AI agents. Covers backend module architecture, ORM models and fields, API decorators, recordset operations, actions, performance patterns, testing, and built-in mixins. Use when building, extending, or debugging Odoo 17.0 custom modules. Triggers on tasks involving __manifest__.py, models.Model, @api decorators, XML views, ir.actions, ir.cron, mail.thread, or any Odoo 17.0 framework pattern.
Use when building SwiftUI views, managing state with @Observable, implementing NavigationStack or NavigationSplitView navigation patterns, composing view hierarchies, presenting sheets, wiring TabView, applying SwiftUI best practices, or structuring an MV-pattern app. Covers view architecture, state management, navigation, view composition, layout, List, Form, Grid, theming, environment, deep links, async loading, and performance.
Debug iOS apps and profile performance using LLDB, Memory Graph Debugger, and Instruments. Use when diagnosing crashes, memory leaks, retain cycles, main thread hangs, slow rendering, build failures, or when profiling CPU, memory, energy, and network usage.
Use when evaluating individual Xiaohongshu post performance, identifying what makes content succeed or fail, extracting viral content patterns, recognizing underperforming content that needs optimization, or comparing performance across different content types and formats
Systematic LLM prompt engineering: analyzes existing prompts for failure modes, generates structured variants (direct, few-shot, chain-of-thought), designs evaluation rubrics with weighted criteria, and produces test case suites for comparing prompt performance. Triggers on: "prompt engineering", "prompt lab", "generate prompt variants", "A/B test prompts", "evaluate prompt", "optimize prompt", "write a better prompt", "prompt design", "prompt iteration", "few-shot examples", "chain-of-thought prompt", "prompt failure modes", "improve this prompt". Use this skill when designing, improving, or evaluating LLM prompts specifically. NOT for evaluating Claude Code skills or SKILL.md files — use skill-evaluator instead.
Performance optimization specialist for improving application speed and efficiency. Use when investigating performance issues or optimizing code.
Use this skill when crafting LLM prompts, implementing chain-of-thought reasoning, designing few-shot examples, building RAG pipelines, or optimizing prompt performance. Triggers on prompt design, system prompts, few-shot learning, chain-of-thought, prompt chaining, RAG, retrieval-augmented generation, prompt templates, structured output, and any task requiring effective LLM interaction patterns.
React and Next.js performance optimization from Vercel Engineering. Use when building React components, optimizing performance, eliminating waterfalls, reducing bundle size, reviewing code for performance issues, or implementing server/client-side optimizations.
Multi-cycle performance optimization with profiling and bottleneck analysis. Use when optimizing application performance.