convex-optimization
Problem-solving strategies for convex optimization in optimization
convex-backend
Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.
convex-optimization-solver
Solve convex optimization problems efficiently
convex-best-practices
Guidelines for building production-ready Convex apps covering function organization, query patterns, validation, TypeScript usage, error handling, and the Zen of Convex design philosophy
convex-agents
Building AI agents with the Convex Agent component including thread management, tool integration, streaming responses, RAG patterns, and workflow orchestration
convex-component-authoring
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management
convex
Umbrella skill for all Convex development patterns. Routes to specific skills like convex-functions, convex-realtime, convex-agents, etc.
convex-cron-jobs
Scheduled function patterns for background tasks including interval scheduling, cron expressions, job monitoring, retry strategies, and best practices for long-running tasks
convex-file-storage
Complete file handling including upload flows, serving files via URL, storing generated files from actions, deletion, and accessing file metadata from system tables
convex-http-actions
External API integration and webhook handling including HTTP endpoint routing, request/response handling, authentication, CORS configuration, and webhook signature validation
convex-functions
Writing queries, mutations, actions, and HTTP actions with proper argument validation, error handling, internal functions, and runtime considerations
avoid-feature-creep
Prevent feature creep when building software, apps, and AI-powered products. Use this skill when planning features, reviewing scope, building MVPs, managing backlogs, or when a user says "just one more feature." Helps developers and AI agents stay focused, ship faster, and avoid bloated products.
convex-migrations
Schema migration strategies for evolving applications including adding new fields, backfilling data, removing deprecated fields, index migrations, and zero-downtime migration patterns
convex-security-audit
Deep security review patterns for authorization logic, data access boundaries, action isolation, rate limiting, and protecting sensitive operations
convex-schema-validator
Defining and validating database schemas with proper typing, index configuration, optional fields, unions, and migration strategies for schema changes
convex-realtime
Patterns for building reactive apps including subscription management, optimistic updates, cache behavior, and paginated queries with cursor-based loading
convex-security-check
Quick security audit checklist covering authentication, function exposure, argument validation, row-level access control, and environment variable handling
Integrating Stripe Payments
Complete workflow for integrating Stripe payments (subscriptions or one-time) with Convex + Next.js. Includes hosted checkout, webhooks, UI components, and testing. Use when adding payment functionality to a Convex + Next.js app.
convex-realtime
Implement real-time features using Convex reactive queries that automatically update when data changes, enabling live collaboration, instant updates, and reactive UIs without manual polling. Use when building live dashboards, implementing collaborative editing, creating chat applications, showing real-time notifications, building activity feeds, implementing presence indicators, creating reactive search, or any feature requiring instant data synchronization across clients.
Convex Agents Usage Tracking
Tracks LLM token consumption and usage metrics for billing, monitoring, and optimization. Use this to log token usage, calculate costs, generate invoices, and understand which agents or users consume the most resources.
convex-backend
Build real-time, reactive backend applications with Convex using TypeScript queries, mutations, and actions with automatic reactivity and optimistic updates. Use when building real-time collaborative applications, implementing reactive data synchronization, writing serverless backend functions, creating queries that auto-update, implementing mutations with transactional guarantees, handling file uploads with Convex storage, implementing authentication with Convex Auth, designing reactive database schemas, or building applications requiring instant data synchronization.
convex-auth
Implement Convex authentication and authorization patterns with OIDC providers or Convex Auth. Use for auth provider setup, ctx.auth usage, user identity handling, and auth-aware schema patterns. Use proactively when users mention auth, JWT, Clerk/Auth0/WorkOS, or Convex Auth. Examples: - user: "Add auth to Convex" → choose provider and outline setup - user: "Get current user" → use ctx.auth.getUserIdentity and checks - user: "Service-to-service access" → use shared secret pattern
convex-deploy
Implement Convex deployment workflows, environments, and CI/CD configuration. Use for dev/prod/preview deployments, deploy keys, local deployments, environment variables, schema/index rollout safety, and HTTP action URLs. Use proactively when users mention deploy, preview, staging, CI, env vars, or local backend. Examples: - user: "Set up Convex deploy in CI" → configure deploy key + npx convex deploy steps - user: "How do preview deployments work?" → explain preview keys, lifecycle, limits - user: "Deploy to prod safely" → list safe schema/function change patterns - user: "Use local convex" → explain npx convex dev --local and limitations
security-convex
Review Convex security audit patterns for authentication and authorization. Use for auditing query/mutation auth, row-level security, and validators. Use proactively when reviewing Convex apps (convex/ directory present). Examples: - user: "Audit these Convex mutations" → check for missing ctx.auth and input validators - user: "Check for IDOR in Convex queries" → verify ownership checks on document access - user: "Review Convex HTTP actions" → check for signature verification on webhooks - user: "Secure these Convex queries" → implement custom functions for enforced auth - user: "Check for data leaks in subscriptions" → verify filtered result sets
convex-core
Build Convex schemas, queries, mutations, actions, and client usage with strict validators and indexes. Use for data modeling, function authoring, argument/return validation, and performance guidance. Use proactively when work touches convex/schema.ts, functions, or api.* references. Examples: - user: "Design tables for multi-tenant app" → defineSchema/defineTable with indexes - user: "Write a mutation" → args/returns validators + auth checks - user: "Optimize query" → add index and withIndex range expression - user: "Use useQuery" → show generated hook usage
agent-architect
Create and refine OpenCode agents via guided Q&A. Use proactively for agent creation, performance improvement, or configuration design. Examples: - user: "Create an agent for code reviews" → ask about scope, permissions, tools, model preferences, generate AGENTS.md frontmatter - user: "My agent ignores context" → analyze description clarity, allowed-tools, permissions, suggest improvements - user: "Add a database expert agent" → gather requirements, set convex-database-expert in subagent_type, configure permissions - user: "Make my agent faster" → suggest smaller models, reduce allowed-tools, tighten permissions
convex-components
Use Convex Components to add isolated backend features and compose component APIs. Use for installing components, calling component APIs, authoring components, and handling component-specific constraints (Id types, env vars, pagination, auth). Use proactively when users mention components, workpool, workflow, agent component, or reusable backend modules. Examples: - user: "Install the Agent component" → add convex.config.ts + use() + components API - user: "Call component functions" → ctx.runQuery(components.foo.bar, args) - user: "Build a component" → defineComponent, schema, _generated, packaging - user: "Expose component API to clients" → re-export functions with auth
convex-runtime
Implement Convex runtime features: HTTP actions, file storage, search (full text + vector), scheduling (crons + scheduled functions), and RAG patterns. Use for webhooks, uploads, search indexes, vectorSearch actions, and background workflows. Use proactively when users mention HTTP endpoints, files, search, embeddings, or cron/schedule. Examples: - user: "Add full text search" → define searchIndex + withSearchIndex query - user: "Upload files" → generate upload URL and persist storageId - user: "Vector search" → action with ctx.vectorSearch and doc fetch - user: "Run cleanup nightly" → cronJobs + function reference
tbd
Git-native issue tracking (beads), coding guidelines, knowledge injection, and spec-driven planning for AI agents. Drop-in replacement for bd/Beads with simpler architecture. Use for: tracking issues/beads with dependencies, creating bugs/features/tasks, planning specs, implementing features from specs, code reviews, committing code, creating PRs, loading coding guidelines (TypeScript, Python, TDD, golden testing, Convex, monorepo patterns), code cleanup, research briefs, architecture docs, agent handoffs, and checking out third-party library source code. Invoke when user mentions: tbd, beads, bd, shortcuts, issues, bugs, tasks, features, epics, todo, tracking, specs, planning, implementation, validation, guidelines, templates, commit, PR, pull request, code review, testing, TDD, test-driven, golden testing, snapshot testing, TypeScript, Python, Convex, monorepo, cleanup, dead code, refactor, handoff, research, architecture, labels, search, checkout library, source code review, or any workflow shortcut.
Convex Best Practices
Guidelines for building production-ready Convex apps covering function organization, query patterns, validation, TypeScript usage, error handling, and the Zen of Convex design philosophy
Convex HTTP Actions
External API integration and webhook handling including HTTP endpoint routing, request/response handling, authentication, CORS configuration, and webhook signature validation
Convex File Storage
Complete file handling including upload flows, serving files via URL, storing generated files from actions, deletion, and accessing file metadata from system tables
Convex Schema Validator
Defining and validating database schemas with proper typing, index configuration, optional fields, unions, and migration strategies for schema changes
Convex Realtime
Patterns for building reactive apps including subscription management, optimistic updates, cache behavior, and paginated queries with cursor-based loading
Convex Functions
Writing queries, mutations, actions, and HTTP actions with proper argument validation, error handling, internal functions, and runtime considerations
Convex Component Authoring
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management
Convex Security Check
Quick security audit checklist covering authentication, function exposure, argument validation, row-level access control, and environment variable handling
Convex Migrations
Schema migration strategies for evolving applications including adding new fields, backfilling data, removing deprecated fields, index migrations, and zero-downtime migration patterns
Convex Cron Jobs
Scheduled function patterns for background tasks including interval scheduling, cron expressions, job monitoring, retry strategies, and best practices for long-running tasks
Convex Security Audit
Deep security review patterns for authorization logic, data access boundaries, action isolation, rate limiting, and protecting sensitive operations
Convex Agents
Building AI agents with the Convex Agent component including thread management, tool integration, streaming responses, RAG patterns, and workflow orchestration
vercel-ai-elements
This skill provides comprehensive documentation for all 23 Vercel AI Elements components organized by category (Message, Conversation, Input/Interaction, Content Display, AI Processing, Advanced Features). Use when users ask about building AI chatbots, need component documentation, want API references for Vercel AI Elements, or need integration examples with the AI SDK.
Convex Agents Rate Limiting
Controls message frequency and token usage to prevent abuse and manage API budgets. Use this to implement per-user limits, global caps, burst capacity, and token quota management.
ai-elements-workflow
This skill provides guidance for building workflow visualizations using Vercel AI Elements and React Flow. It should be used when implementing interactive node-based interfaces, workflow diagrams, or process flow visualizations in Next.js applications. Covers Canvas, Node, Edge, Connection, Controls, Panel, and Toolbar components.
betterauth-tanstack-convex
Step-by-step guide for setting up Better Auth authentication with Convex and TanStack Start. This skill should be used when configuring authentication in a Convex + TanStack Start project, troubleshooting auth issues, or implementing sign up/sign in/sign out flows. Covers installation, environment variables, SSR authentication, route handlers, and the expectAuth pattern.
convex-mutations
This skill should be used when implementing Convex mutation functions. It provides comprehensive guidelines for defining, registering, calling, and scheduling mutations, including database operations, transactions, and scheduled job patterns.
Convex Agents RAG
Implements Retrieval-Augmented Generation (RAG) patterns to enhance agents with custom knowledge bases. Use this when agents need to search through documents, retrieve context from a knowledge base, or ground responses in specific data.
Convex Agents Human Agents
Integrates human agents into automated workflows for human-in-the-loop interactions. Use this when humans need to respond alongside AI agents, handle escalations, or provide context that AI cannot determine.