convex-seed

Seed or import data into a Convex database using internal mutations or bulk import.

Updated Sep 17, 2026
One-click install
npx skills add https://github.com/Tehzeeb07/CodeRush --skill convex-seed-tehzeeb07
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: convex-seed
Source: https://github.com/Tehzeeb07/CodeRush/tree/main/.agents/skills/convex-seed
Command: npx skills add https://github.com/Tehzeeb07/CodeRush --skill convex-seed-tehzeeb07

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Populating a Convex database with initial or test data is repetitive and error-prone when done manually, and re-running seed scripts can create duplicates or inconsistent state. ## Core Features & Use Cases - Fixture Seeding via internalMutation: Write a re-runnable internal mutation that inserts sample rows matching your schema validators, then execute it with npx convex run. - Bulk Data Import: Shape existing datasets to match the schema and load them with npx convex import. - Idempotent Seeding: Use clear-then-insert or upsert patterns so re-running the seed never corrupts data. - Use Case: You just defined a new tasks table in your Convex schema and need realistic sample rows for local development. Create an idempotent seed mutation, run it, and verify row counts before sharing the deployment. ## Quick Start Ask the AI to create an idempotent Convex seed mutation for your schema and run it with npx convex run.

Frequently Asked Questions about convex-seed

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I seed data into a Convex database?▼

Write an internalMutation that inserts sample rows matching your schema validators, then execute it with npx convex run. For larger datasets, shape the data to the schema and use npx convex import instead.

How do I make a Convex seed function idempotent?▼

Use a clear-then-insert or upsert pattern inside the seed mutation so re-running it produces the same final state. This prevents duplicate rows when the seed is executed multiple times during development.

When should I use npx convex import instead of a seed mutation?▼

Use npx convex import for bulk loading of existing datasets that already match your schema. Use an internalMutation seed function for programmatically generated fixtures that need to be re-runnable.

Can I seed test data with secrets or PII into Convex?▼

No. Never seed secrets or personally identifiable information into a shared Convex deployment. Use synthetic or anonymized fixture data so other developers with deployment access are not exposed to sensitive values.

How do I verify Convex seeding worked correctly?▼

Check row counts in the affected tables after running the seed mutation or import. Comparing expected versus actual counts confirms the inserts matched the schema and completed without partial failures.