server-components
Guidance on React Server Components (RSC) in Next.js, covering server/client component boundaries, data fetching, and composition patterns.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
293 skills found
Guidance on React Server Components (RSC) in Next.js, covering server/client component boundaries, data fetching, and composition patterns.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Generate high-quality images via a local ComfyUI instance. Perfect for private workflows and professional-grade AI image synthesis.
Orchestrates complex programming tasks by analyzing available skills, generating structured execution plans, and managing manual or delegated multi-step workflows.
Foundational architectural principles for MoAI-ADK, featuring TRUST 5, SPEC-First TDD, delegation patterns, and token-efficient agent orchestration workflows.
Unified Python CLI for Tavily AI operations including web search, URL extraction, site crawling, link mapping, and automated deep research reports.
Analyze your product and codebase to identify, qualify, and rank high-potential business leads with actionable outreach strategies.
Generate publication-quality statistical plots from CSV or JSON data files using AI-driven automated visualization.
Summon framework expert: assisting with Kotlin Multiplatform UI development, type-safe modifiers, state management, routing, and SSR for web and JVM applications.
End-to-end GitHub repository maintenance agent. Automates triage, PR review, issue analysis, and maintenance reporting to ensure long-term repository health, stability, and growth.
An AI-powered sales assistant that transforms business scenarios into optimized prompts, automatically generating high-quality emails, proposals, and analysis reports without requiring prompt engineering skills.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.