Production-ready Convex patterns for function organization, validation, query optimization, TypeScript safety, and error handling.
Works with
Covers five core areas: function organization by domain, argument and return type validation, indexed query patterns, ConvexError handling, and write conflict avoidance through idempotent mutations
Enforces code quality via @convex-dev/eslint-plugin with four rules covering function syntax, validators, table IDs, and runtime imports
Includes complete CRUD
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionconvex-best-practicesExecute the skills CLI command in your project's root directory to begin installation:
Fetches convex-best-practices from waynesutton/convexskills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate convex-best-practices. Access via /convex-best-practices in your agent's command palette.
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.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Build production-ready Convex applications by following established patterns for function organization, query optimization, validation, TypeScript usage, and error handling.
All patterns in this skill comply with @convex-dev/eslint-plugin. Install it for build-time validation:
npm i @convex-dev/eslint-plugin --save-dev
// eslint.config.js
import { defineConfig } from "eslint/config";
import convexPlugin from "@convex-dev/eslint-plugin";
export default defineConfig([
...convexPlugin.configs.recommended,
]);
The plugin enforces four rules:
| Rule | What it enforces |
|---|---|
no-old-registered-function-syntax |
Object syntax with handler |
require-argument-validators |
args: {} on all functions |
explicit-table-ids |
Table name in db operations |
import-wrong-runtime |
No Node imports in Convex runtime |
Docs: https://docs.convex.dev/eslint
Before implementing, do not assume; fetch the latest documentation:
Organize your Convex functions by domain:
// convex/users.ts - User-related functions
import { query, mutation } from "./_generated/server";
import { v } from "convex/values";
export const get = query({
args: { userId: v.id("users") },
returns: v.union(
v.object({
_id: v.id("users"),
_creationTime: v.number(),
name: v.string(),
email: v.string(),
}),
v.null(),
),
handler: async (ctx, args) => {
return await ctx.db.get("users", args.userId);
},
});
Always define validators for arguments AND return types:
export const createTask = mutation({
args: {
title: v.string(),
description: v.optional(v.string()),
priority: v.union(v.literal("low"), v.literal("medium"), v.literal("high")),
},
returns: v.id("tasks"),
handler: async (ctx, args) => {
return await ctx.db.insert("tasks", {
title: args.title,
description: args.description,
priority: args.priority,
completed: false,
createdAt: Date.now(),
});
},
});
Use indexes instead of filters for efficient queries:
// Schema with index
export default defineSchema({
tasks: defineTable({
userId: v.id("users"),
status: v.string(),
createdAt: v.number(),
})
.index("by_user", ["userId"])
.index("by_user_and_status", ["userId", "status"]),
});
// Query using index
export const getTasksByUser = query({
args: { userId: v.id("users") },
returns: v.array(
v.object({
_id: v.id("tasks"),
_creationTime: v.number(),
userId: v.id("users"),
status: v.string(),
createdAt: v.number(),
}),
),
handler: async (ctx, args) => {
return await ctx.db
.query("tasks")
.withIndex("by_user", (q) => q.eq("userId", args.userId))
.order("desc")
.collect();
},
});
Use ConvexError for user-facing errors:
import { ConvexError } from "convex/values";
export const updateTask = mutation({
args: {
taskId: v.id("tasks"),
title: v.string(),
},
returns: v.null(),
handlerMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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I recommend convex-best-practices for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in convex-best-practices — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: convex-best-practices is focused, and the summary matches what you get after install.
I recommend convex-best-practices for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in convex-best-practices — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: convex-best-practices is the kind of skill you can hand to a new teammate without a long onboarding doc.
convex-best-practices is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
convex-best-practices reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for convex-best-practices matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend convex-best-practices for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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