ai-elements-chatbot
This skill provides production-ready AI chat UI components built on shadcn/ui for conversational AI interfaces. Use when building ChatGPT-style chat interfaces with streaming responses, tool/function call displays, reasoning visualization, or source citations. Provides 30+ components including Message, Conversation, Response, CodeBlock, Reasoning, Tool, Actions, Sources optimized for Vercel AI SDK v5. Prevents common setup errors with Next.js App Router, Tailwind v4, shadcn/ui integration, AI SDK v5 migration, component composition patterns, voice input browser compatibility, responsive design issues, and streaming optimization. Keywords: ai-elements, vercel-ai-sdk, shadcn, chatbot, conversational-ai, streaming-ui, chat-interface, ai-chat, message-components, conversation-ui, tool-calling, reasoning-display, source-citations, markdown-streaming, function-calling, ai-responses, prompt-input, code-highlighting, web-preview, branch-navigation, thinking-display, perplexity-style, claude-artifacts
ralph-loop-creator
Generate structured prompts for autonomous AI work. Creates PROMPT.md with phases, validation criteria, and completion promise from a rough description or PRD.
ai-integrated-api-backend
Comprehensive guide for building production-grade AI-integrated backends with multi-provider support, intelligent fallback mechanisms, region configuration, prompt management with variables/tools, and session-based billing. Use when implementing AI features in Django/Python backends or designing LLM-powered API architectures with external data integration.
geo-optimizer
This skill should be used when the user asks to "audit for AI visibility", "optimize for ChatGPT", "check GEO readiness", "analyze hedge density", "generate agentfacts", "check if my site works with AI search", "test LLM crawlability", "check discovery gap", or mentions Generative Engine Optimization, AI crawlers, Perplexity discoverability, or NANDA protocol.
faf-expert
Expert in .faf (Foundational AI-context Format) files for persistent project context. Use when working with .faf files, project DNA, CLAUDE.md bi-sync, faf-cli commands, MCP server configuration, or AI-readiness scoring (0-100%). Updated for v2.8.0 Tool Visibility System.
security-incident-playbook-generator
Creates response procedures for security incidents with containment steps, communication templates, and evidence collection. Use for "incident response", "security playbook", "breach response", or "IR plan".
cloudflare-ai-gateway
Cloudflare AI Gateway for unified interface to AI providers with caching, rate limiting, and analytics
prompt-template-builder
Creates reusable prompt templates with strict output contracts, style rules, few-shot examples, and do/don't guidelines. Provides system/user prompt files, variable placeholders, output formatting instructions, and quality criteria. Use when building "prompt templates", "LLM prompts", "AI system prompts", or "prompt engineering".
langchainjs
LangChain.js - TypeScript framework for building LLM-powered applications with agents, chains, RAG, tools, memory, and integrations for OpenAI, Anthropic, Google, and hundreds of other providers
agentv-eval-builder
Create and maintain AgentV YAML evaluation files for testing AI agent performance. Use this skill when creating new eval files, adding eval cases, or configuring custom evaluators (code validators or LLM judges) for agent testing workflows.
cost-latency-optimizer
Reduces LLM costs and improves response times through caching, model selection, batching, and prompt optimization. Provides cost breakdowns, latency hotspots, and configuration recommendations. Use for "cost reduction", "performance optimization", "latency improvement", or "efficiency".
dev-swarm-mcp-server
Add and manage Model Context Protocol (MCP) servers for AI agents, including transports, scopes, and config files. Use when extending agent capabilities with new tools or data sources.
scaffold-rules
Scaffold development rules for AI coding agents. Auto-invoked when user asks about setting up rules, coding conventions, or configuring their AI agent environment.
ai-sdk-ui
Frontend React hooks for AI-powered chat interfaces, completions, and streaming UIs with Vercel AI SDK v5. Includes useChat, useCompletion, and useObject hooks for building interactive AI applications. Use when: building React chat interfaces, implementing AI completions in UI, streaming AI responses to frontend, handling chat message state, building Next.js AI apps, managing file attachments with AI, or encountering errors like "useChat failed to parse stream", "useChat no response", unclosed streams, or streaming issues. Keywords: ai sdk ui, useChat hook, useCompletion hook, useObject hook, react ai chat, ai chat interface, streaming ai ui, nextjs ai chat, vercel ai ui, react streaming, ai sdk react, chat message state, ai file attachments, message persistence, useChat error, streaming failed ui, parse stream error, useChat no response, react ai hooks, nextjs app router ai, nextjs pages router ai
context-manager
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.
agent-creator
Create composable AI agent systems in NestJS projects following the "tools all the way down" architecture. Use this skill when users want to: (1) Create new AI agents with orchestrator/planner/executor/evaluator components, (2) Build agentic systems that can call other agents as tools, (3) Implement DAG-based planning with parallel execution, (4) Add database-backed state persistence for agent runs, (5) Create custom evaluators for quality assurance. Triggers on "create agent", "build agent", "agent system", "agentic", "orchestrator", "planner/executor pattern", or NestJS AI agent requests.
rag-implementation
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.