🎯Skills21
A step-by-step guide for integrating Better Auth authentication with Convex backend and TanStack Start framework, covering installation, environment variables, SSR authentication, and route handlers.
A Convex + TanStack Start skill providing comprehensive guidance for building reactive, real-time full-stack applications with schema design, authentication, and SSR patterns.
Skill for implementing Convex query functions with guidance on function definition, registration, pagination, indexing, full text search, and query optimization using the new function syntax.
Comprehensive guidance for Convex actions, HTTP endpoints, validators, schema design, file storage, environment variables, scheduling, and TypeScript best practices. Covers function definitions, API design, database limits, and advanced Convex features including cron jobs and full-text search.
A skill for building tool-enabled Convex agents that can query databases, call external APIs, and perform multi-step operations. Provides patterns for defining tools with Zod validation and configuring autonomous agent behavior.
Implements Retrieval-Augmented Generation (RAG) patterns for Convex agents, enabling semantic search through custom knowledge bases with namespace-based multi-tenant isolation for user- or team-specific data.
A skill that provides specialized guidance for implementing Convex mutation functions, covering function definition, registration, database operations (insert, patch, replace, delete), transactions, and scheduled job patterns.
Teaches how to stream Convex agent responses in real-time to clients without blocking, covering async streaming setup, stream chunking configuration, delta retrieval, and best practices for responsive chat UIs and long-running generations.
A skill for orchestrating multi-step agent operations on the Convex platform with durable execution, automatic retries, and failure recovery, enabling workflows that survive server restarts and coordinate multiple agents.
A foundational skill for setting up and configuring Convex agents for chat-based AI interactions, covering agent initialization, conversation thread management, and text or structured response generation from LLMs.
A skill for building interactive workflow visualizations using Vercel AI Elements and React Flow in Next.js applications. Covers Canvas, Node, Edge, Connection, Controls, Panel, and Toolbar components for node-based diagram interfaces.
A skill for sending, saving, retrieving, and managing messages within Convex agent conversations, supporting user message handling, conversation history display, and UIMessages for rich rendering.
A skill for setting up a graphical playground to test, debug, and develop Convex agents, allowing users to browse threads, send messages, inspect tool calls, and configure context parameters without writing code.
A skill for tracking LLM token consumption and usage metrics in Convex applications, enabling accurate billing, cost monitoring, usage analysis by user or agent, and invoice generation.
A skill for managing conversation threads in the Convex Agent framework, providing patterns for creating threads, grouping messages into linear histories, managing per-user conversation records, and handling thread metadata.
A Convex skill for handling file uploads, image attachments, and media processing in agent conversations. Covers uploading, storing, attaching files to messages, and managing file lifecycle including DALL-E image generation.
A Convex Agents skill for customizing the context provided to the LLM during each generation, including cross-thread search, RAG context injection, memory management, conversation summarization, and message filtering.
Integrates human agents into Convex-based automated workflows for human-in-the-loop interactions, enabling support escalations, approval workflows, and human-AI collaboration.
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A Convex Agents skill that implements rate limiting to control message frequency and token usage, preventing abuse and managing API budgets. Supports per-user limits, global caps, burst capacity, and token quota management using fixed-window and token-bucket algorithms.
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