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Found 109 Skills
Expert guide for managing application configuration including environment variables, config files, secrets management, and multi-environment setups. Use when handling .env files, config validation, or configuration architecture.
Design MCP prompts to expose reusable prompt templates. Use when creating parameterized prompts in xmcp.
Guide for making changes to the database schema, validation, types, and data access layer. Use when adding tables, columns, relations, or modifying the data model. Triggers on: add table, add column, modify schema, database change, data model, new entity, schema migration.
Centralized environment variable management with validation. Fail fast at startup if config is invalid. Supports multi-environment setups (dev/staging/prod) with type-safe access.
Create AI tools for use with Vercel AI SDK agents. Use when asked to "create AI tools", "add agent tools", "create tool for AI", or "add tools to agent".
Complete environment variable management with type-safe validation, Vercel dev workflow, and prebuild validation.
Advanced TypeScript patterns and best practices for 2025
Registers existing React components with Tambo so AI can render them. Use when user wants to make their existing components available to AI, register components for generative UI, convert React components to Tambo components, or mentions /add-components-to-registry. For creating NEW components, see the components skill. For project setup, use add-to-existing-project or start-from-scratch skills.
Configure TypeScript strict mode with additional safety flags. Catch bugs at compile time instead of production. Includes branded types, exhaustive switches, and Result types.
Type-safe development patterns for JARVIS AI Assistant
Creates and registers Tambo components - generative (AI creates on-demand) and interactable (pre-placed, AI updates). Use when defining components, working with TamboComponent, withInteractable, propsSchema, or registering components for AI to render or update.
Designs robust function/tool calling schemas for LLMs with JSON schemas, validation strategies, typed interfaces, and example calls. Use when implementing "function calling", "tool use", "LLM tools", or "agent actions".