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Found 1,950 Skills
React performance optimization specialist. Expert in DevTools Profiler, memoization, Core Web Vitals, bundle optimization, and virtualization. Use this skill for performance bottlenecks, slow renders, large bundles, or memory issues in React applications.
Core Web Vitals optimization for LCP, INP, CLS with 2026 thresholds, performance budgets, and RUM. Use when improving page performance, diagnosing CWV regressions, or setting performance budgets.
Expertise in Go programming according to the Google Go Best Practices. Focuses on actionable advice for naming, error handling, performance, testing, and general idiomatic Go to ensure high-quality, maintainable, and efficient codebases.
Implements search and filter interfaces for both frontend (React/TypeScript) and backend (Python) with debouncing, query management, and database integration. Use when adding search functionality, building filter UIs, implementing faceted search, or optimizing search performance.
Optimizing vector embeddings for RAG systems through model selection, chunking strategies, caching, and performance tuning. Use when building semantic search, RAG pipelines, or document retrieval systems that require cost-effective, high-quality embeddings.
Local LLM inference with Ollama. Use when setting up local models for development, CI pipelines, or cost reduction. Covers model selection, LangChain integration, and performance tuning.
Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.
Query Google Search Console for SEO data - search queries, top pages, CTR opportunities, URL inspection, and sitemaps. Use when analyzing search performance, finding optimization opportunities, or checking indexing status.
Systematic debugging methodology with root cause analysis. Phases: investigate, hypothesize, validate, verify. Capabilities: backward call stack tracing, multi-layer validation, verification protocols, symptom analysis, regression prevention. Actions: debug, investigate, trace, analyze, validate, verify bugs. Keywords: debugging, root cause, bug fix, stack trace, error investigation, test failure, exception handling, breakpoint, logging, reproduce, isolate, regression, call stack, symptom vs cause, hypothesis testing, validation, verification protocol. Use when: encountering bugs, analyzing test failures, tracing unexpected behavior, investigating performance issues, preventing regressions, validating fixes before completion claims.
Generate analytics reports from Olakai data using CLI commands. AUTO-INVOKE when user wants: usage summaries, KPI trends, risk analysis, ROI reports, efficiency metrics, agent comparisons, token usage reports, cost analysis, compliance reports, or any analytics without using the web dashboard. TRIGGER KEYWORDS: olakai, analytics, reports, usage summary, KPI trends, risk analysis, ROI, efficiency, agent comparison, token usage, cost analysis, metrics report, dashboard data, CLI analytics, terminal report, compliance, usage report, event summary, performance metrics, AI usage stats. DO NOT load for: setting up monitoring (use olakai-add-monitoring), troubleshooting (use olakai-troubleshoot), or creating new agents (use olakai-create-agent).
Expert prompt optimization for LLMs and AI systems. Use when building AI features, improving agent performance, crafting system prompts, or optimizing LLM interactions. Masters prompt patterns and techniques.
Write idiomatic Go with goroutines, channels, and interfaces. Use for Go development, concurrency, or performance.