convex-create-component
Design and build isolated, reusable Convex backend components with clear boundaries and app-facing wrappers.
Works with
0
total installs
0
this week
21
GitHub stars
0
upvotes
Install Skill
Run in your terminal
0
installs
0
this week
21
stars
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
Installation Guide
How to use convex-create-component on Cursor
AI-first code editor with Composer
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
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches convex-create-component from get-convex/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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
- 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.
- Choose the shape using the decision tree below and read the matching reference file.
- 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.
- 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
- Create the component structure with
convex.config.ts,schema.ts, and function files. - Implement functions using the component's own
./_generated/serverimports, not the app's generated files. - Wire the component into the app with
app.use(...). If the app does not already haveconvex/convex.config.ts, create it. - Call the component from the app through
components.<name>usingctx.runQuery,ctx.runMutation, orctx.runAction. - If React clients, HTTP callers, or public APIs need access, create wrapper functions in the app instead of exposing component functions directly.
- Run
npx convex devand 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 ownconvex.config.ts - Install it from the app's
convex/convex.config.tswithapp.use(...) - Let
npx convex devgenerate 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) => List & Monetize Your Skill
Submit your Claude Code skill and start earning
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
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Related Skills
grill-me
386mattpocock/skills
premortem
197parcadei/continuous-claude-v3
deslop
118cursor/plugins
framer-motion
98pproenca/dot-skills
write-a-prd
91mattpocock/skills
travel-planner
90ailabs-393/ai-labs-claude-skills
Reviews
- KKwame Chawla★★★★★Dec 28, 2024
convex-create-component has been reliable in day-to-day use. Documentation quality is above average for community skills.
- XXiao Harris★★★★★Dec 24, 2024
Solid pick for teams standardizing on skills: convex-create-component is focused, and the summary matches what you get after install.
- MMin Okafor★★★★★Dec 24, 2024
I recommend convex-create-component for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- MMia Smith★★★★★Dec 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.
- MMia Liu★★★★★Dec 20, 2024
Registry listing for convex-create-component matched our evaluation — installs cleanly and behaves as described in the markdown.
- NNaina Huang★★★★★Dec 4, 2024
Useful defaults in convex-create-component — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAnika Gupta★★★★★Nov 27, 2024
convex-create-component is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- MMia Diallo★★★★★Nov 23, 2024
Registry listing for convex-create-component matched our evaluation — installs cleanly and behaves as described in the markdown.
- NNikhil Ghosh★★★★★Nov 19, 2024
convex-create-component fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- NNikhil Gill★★★★★Nov 15, 2024
We added convex-create-component from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
showing 1-10 of 63
Discussion
Comments — not star reviews- No comments yet — start the thread.