convex-create-component

Design and build isolated, reusable Convex backend components with clear boundaries and app-facing wrappers.

get-convex/agent-skillsUpdated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/get-convex/agent-skills --skill convex-create-component

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installs

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this week

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What it does

  • Supports three component shapes: local (single-app), packaged (npm), and hybrid (both), with a decision tree to choose the right fit

  • Enforces architectural boundaries: components own their tables and functions, while the app handles authentication, environment access, and client-facing wrappers

  • Provides a complete workflow from planning (tables, public API, data flow) through

Category

Productivity

Last updated

Apr 8, 2026

Installation Guide

How to use convex-create-component on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add convex-create-component
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/get-convex/agent-skills --skill convex-create-component

Fetches convex-create-component from get-convex/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/convex-create-component

Restart Cursor to activate convex-create-component. Access via /convex-create-component in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

Convex Create Component

Create reusable Convex components with clear boundaries and a small app-facing API.

When to Use

  • Creating a new Convex component in an existing app
  • Extracting reusable backend logic into a component
  • Building a third-party integration that should own its own tables and workflows
  • Packaging Convex functionality for reuse across multiple apps

When Not to Use

  • One-off business logic that belongs in the main app
  • Thin utilities that do not need Convex tables or functions
  • App-level orchestration that should stay in convex/
  • Cases where a normal TypeScript library is enough

Workflow

  1. Ask the user what they are building and what the end goal is. If the repo already makes the answer obvious, say so and confirm before proceeding.
  2. Choose the shape using the decision tree below and read the matching reference file.
  3. Decide whether a component is justified. Prefer normal app code or a regular library if the feature does not need isolated tables, backend functions, or reusable persistent state.
  4. Make a short plan for:
    • what tables the component owns
    • what public functions it exposes
    • what data must be passed in from the app (auth, env vars, parent IDs)
    • what stays in the app as wrappers or HTTP mounts
  5. Create the component structure with convex.config.ts, schema.ts, and function files.
  6. Implement functions using the component's own ./_generated/server imports, not the app's generated files.
  7. Wire the component into the app with app.use(...). If the app does not already have convex/convex.config.ts, create it.
  8. Call the component from the app through components.<name> using ctx.runQuery, ctx.runMutation, or ctx.runAction.
  9. If React clients, HTTP callers, or public APIs need access, create wrapper functions in the app instead of exposing component functions directly.
  10. Run npx convex dev and fix codegen, type, or boundary issues before finishing.

Choose the Shape

Ask the user, then pick one path:

Goal Shape Reference
Component for this app only Local references/local-components.md
Publish or share across apps Packaged references/packaged-components.md
User explicitly needs local + shared library code Hybrid references/hybrid-components.md
Not sure Default to local references/local-components.md

Read exactly one reference file before proceeding.

Default Approach

Unless the user explicitly wants an npm package, default to a local component:

  • Put it under convex/components/<componentName>/
  • Define it with defineComponent(...) in its own convex.config.ts
  • Install it from the app's convex/convex.config.ts with app.use(...)
  • Let npx convex dev generate the component's own _generated/ files

Component Skeleton

A minimal local component with a table and two functions, plus the app wiring.

// convex/components/notifications/convex.config.ts
import { defineComponent } from "convex/server";

export default defineComponent("notifications");
// convex/components/notifications/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  notifications: defineTable({
    userId: v.string(),
    message: v.string(),
    read: v.boolean(),
  }).index("by_user", ["userId"]),
});
// convex/components/notifications/lib.ts
import { v } from "convex/values";
import { mutation, query } from "./_generated/server.js";

export const send = mutation({
  args: { userId: v.string(), message: v.string() },
  returns: v.id("notifications"),
  handler: async (ctx, args) => {
    return await ctx.db.insert("notifications", {
      userId: args.userId,
      message: args.message,
      read: false,
    });
  },
});

export const listUnread = query({
  args: { userId: v.string() },
  returns: v.array(
    v.object({
      _id: v.id("notifications"),
      _creationTime: v.number(),
      userId: v.string(),
      message: v.string(),
      read: v.boolean(),
    })
  ),
  handler: async (ctx, args) => {
    return await ctx.db
      .query("notifications")
      .withIndex("by_user", (q) => q.eq("userId", args.userId))
      .filter((q) => q.eq(q.field("read"), false))
      .collect();
  },
});
// convex/convex.config.ts
import { defineApp } from "convex/server";
import notifications from "./components/notifications/convex.config.js";

const app = defineApp();
app.use(notifications);

export default app;
// convex/notifications.ts  (app-side wrapper)
import { v } from "convex/values";
import { mutation, query } from "./_generated/server";
import { components } from "./_generated/api";
import { getAuthUserId } from "@convex-dev/auth/server";

export const sendNotification = mutation({
  args: { message: v.string() },
  returns: v.null(),
  handler: async (ctx, args) => {
    const userId = await getAuthUserId(ctx);
    if (!userId) throw new Error("Not authenticated");

    await ctx.runMutation(components.notifications.lib.send, {
      userId,
      message: args.message,
    });
    return null;
  },
});

export const myUnread = query({
  args: {},
  handler: async (ctx) => 

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Steps

  1. 1Install product management skill
  2. 2Start with user story generation for known feature
  3. 3Progress to competitive analysis: research 2-3 competitors
  4. 4Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5Draft stakeholder communications and refine based on feedback
  6. 6Build template library for recurring PM tasks
  7. 7Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use when

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid when

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Related Skills

Reviews

4.863 reviews
  • K
    Kwame ChawlaDec 28, 2024

    convex-create-component has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • X
    Xiao HarrisDec 24, 2024

    Solid pick for teams standardizing on skills: convex-create-component is focused, and the summary matches what you get after install.

  • M
    Min OkaforDec 24, 2024

    I recommend convex-create-component for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • M
    Mia SmithDec 24, 2024

    Keeps context tight: convex-create-component is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • M
    Mia LiuDec 20, 2024

    Registry listing for convex-create-component matched our evaluation — installs cleanly and behaves as described in the markdown.

  • N
    Naina HuangDec 4, 2024

    Useful defaults in convex-create-component — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • A
    Anika GuptaNov 27, 2024

    convex-create-component is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • M
    Mia DialloNov 23, 2024

    Registry listing for convex-create-component matched our evaluation — installs cleanly and behaves as described in the markdown.

  • N
    Nikhil GhoshNov 19, 2024

    convex-create-component fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • N
    Nikhil GillNov 15, 2024

    We added convex-create-component from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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