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Topic: react

760 skills in this topic.

mcp-apps Build MCP App servers that deliver interactive HTML user interfaces to hosts like Claude.ai and ChatGPT. Use when creating MCP servers with UI resources, building interactive tools with visual output, or implementing bidirectional communication between iframe UIs and MCP hosts. Covers the ui:// resource scheme, tool-UI linkage, postMessage JSON-RPC transport, CSP security, and sandbox architecture. Triggers on: "MCP app", "MCP UI", "ui:// resource", "interactive MCP tool", "MCP server with interface", "MCP iframe".
connorads/lumo-mcp-app 1
chatgpt-app-builder Guide developers through creating ChatGPT apps. Covers the full lifecycle: brainstorming ideas against UX guidelines, bootstrapping projects, implementing tools/widgets, debugging, running dev servers, deploying and connecting apps to ChatGPT. Use when a user wants to create or update a ChatGPT app / MCP server for ChatGPT, or use the Skybridge framework.
connorads/lumo-mcp-app 1
creating-styled-wrappers Creates styled wrapper components that compose headless/base compound components. Use when refactoring styled components to use base primitives, implementing opinionated design systems on top of headless components, or when the user mentions "use base components", "compose primitives", "styled wrapper", or "refactor to use base".
tambo-ai/tambo 11,120
ai-sdk-model-manager Manages AI SDK model configurations - updates packages, identifies missing models, adds new models with research, and updates documentation
tambo-ai/tambo 11,120
building-compound-components Creates unstyled compound components that separate business logic from styles. Use when building headless UI primitives, creating component libraries, implementing Radix-style namespaced components, or when the user mentions "compound components", "headless", "unstyled", "primitives", or "render props".
tambo-ai/tambo 11,120
building-settings-ui Use this skill when adding or modifying settings UI in Tambo Cloud. Covers where a new settings section belongs (Agent tab vs Settings tab), and the component patterns used across both pages (card layout, toasts, confirmation dialogs, destructive styling, save behavior conventions). Triggers on "add a new settings section", "where should X go?", "settings UI", "settings page", "agent page", or any work touching apps/web/components/dashboard-components/project-details/, project-settings.tsx, or agent-settings.tsx. Not for full-stack feature building (DB, tRPC, tests); those patterns will get their own skills.
tambo-ai/tambo 11,120
generative-ui Creates a new Tambo generative UI app from scratch. Scaffolds with tambo create-app, wires TamboProvider, registers starter components. Triggers on "new Tambo app", "create a generative UI app", "build an AI app from scratch", "start a new project with Tambo". For existing apps, use building-with-tambo.
tambo-ai/tambo 11,120
building-with-tambo Integrates Tambo into existing React apps — detects tech stack, installs @tambo-ai/react, wires TamboProvider, registers components with Zod schemas, and sets up tools/context. Use when adding AI-powered generative UI to an existing codebase. Triggers on "add Tambo", "integrate Tambo", "add AI chat to my app", "add generative UI", or when the user has an existing React/Next.js/Vite project and wants to add AI-powered components. For brand-new projects, use generative-ui instead.
tambo-ai/tambo 11,120
validating-accessibility Use this skill when creating, modifying, or reviewing any .tsx component in apps/web, even if the user doesn't mention "accessibility." Covers semantic HTML, aria labels, navigation landmarks, forms, dialogs, and keyboard navigation. Trigger on: adding buttons, links, toggles, icons, or any interactive element; building or editing forms; adding dialogs or modals; reviewing UI code. Includes inline verification patterns for scanning violations. Not for styling or layout changes that don't involve interactive elements.
tambo-ai/tambo 11,120
api-resource-lifecycle Guides CRUD operations for API resources with cascading dependencies, descriptive validation, and orphan prevention. Use when adding delete/remove operations, creating validation logic, building resources that depend on other resources, or when the user mentions "cascade delete", "orphan records", "duplicate detection", "validation errors", "resource cleanup", or "rollback on failure".
tambo-ai/tambo 11,120
building-forms Builds form components and data collection interfaces including contact forms, registration flows, checkout processes, surveys, and settings pages. Includes 50+ input types, validation strategies, accessibility patterns (WCAG 2.1), multi-step wizards, and UX best practices. Provides decision trees from data type to component selection, validation timing guidance, and error handling patterns. Use when creating forms, collecting user input, building surveys, implementing validation, designing multi-step workflows, or ensuring form accessibility.
ancoleman/ai-design-components 333
deploying-on-aws Selecting and implementing AWS services and architectural patterns. Use when designing AWS cloud architectures, choosing compute/storage/database services, implementing serverless or container patterns, or applying AWS Well-Architected Framework principles.
ancoleman/ai-design-components 333
writing-github-actions Write GitHub Actions workflows with proper syntax, reusable workflows, composite actions, matrix builds, caching, and security best practices. Use when creating CI/CD workflows for GitHub-hosted projects or automating GitHub repository tasks.
ancoleman/ai-design-components 333
managing-configuration Guide users through creating, managing, and testing server configuration automation using Ansible. When automating server configurations, deploying applications with Ansible playbooks, managing dynamic inventories for cloud environments, or testing roles with Molecule, this skill provides idempotency patterns, secrets management with ansible-vault and HashiCorp Vault, and GitOps workflows for configuration as code.
ancoleman/ai-design-components 333
implementing-realtime-sync Real-time communication patterns for live updates, collaboration, and presence. Use when building chat applications, collaborative tools, live dashboards, or streaming interfaces (LLM responses, metrics). Covers SSE (server-sent events for one-way streams), WebSocket (bidirectional communication), WebRTC (peer-to-peer video/audio), CRDTs (Yjs, Automerge for conflict-free collaboration), presence patterns, offline sync, and scaling strategies. Supports Python, Rust, Go, and TypeScript.
ancoleman/ai-design-components 333
managing-git-workflows Manage Git branching strategies, commit conventions, and collaboration workflows. Use when choosing between trunk-based development, GitHub Flow, or GitFlow, implementing conventional commits for automated versioning, setting up Git hooks for quality gates, or organizing monorepos with clear ownership.
ancoleman/ai-design-components 333
deploying-on-azure Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
ancoleman/ai-design-components 333
writing-dockerfiles Writing optimized, secure, multi-stage Dockerfiles with language-specific patterns (Python, Node.js, Go, Rust), BuildKit features, and distroless images. Use when containerizing applications, optimizing existing Dockerfiles, or reducing image sizes.
ancoleman/ai-design-components 333
building-clis Build professional command-line interfaces in Python, Go, and Rust using modern frameworks like Typer, Cobra, and clap. Use when creating developer tools, automation scripts, or infrastructure management CLIs with robust argument parsing, interactive features, and multi-platform distribution.
ancoleman/ai-design-components 333
resource-tagging Apply and enforce cloud resource tagging strategies across AWS, Azure, GCP, and Kubernetes for cost allocation, ownership tracking, compliance, and automation. Use when implementing cloud governance, optimizing costs, or automating infrastructure management.
ancoleman/ai-design-components 333
using-vector-databases Vector database implementation for AI/ML applications, semantic search, and RAG systems. Use when building chatbots, search engines, recommendation systems, or similarity-based retrieval. Covers Qdrant (primary), Pinecone, Milvus, pgvector, Chroma, embedding generation (OpenAI, Voyage, Cohere), chunking strategies, and hybrid search patterns.
ancoleman/ai-design-components 333
implementing-observability Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.
ancoleman/ai-design-components 333
managing-dns Manage DNS records, TTL strategies, and DNS-as-code automation for infrastructure. Use when configuring domain resolution, automating DNS from Kubernetes with external-dns, setting up DNS-based load balancing, or troubleshooting propagation issues across cloud providers (Route53, Cloud DNS, Azure DNS, Cloudflare).
ancoleman/ai-design-components 333
visualizing-data Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
ancoleman/ai-design-components 333