Convex Seed

Reach for convex-seed when you need fixture data in a fresh Convex deployment or a one-time bulk load from a file. The skill steers you toward an internalMutation seed function you can re-run with `npx convex run`, or `npx convex import` for larger datasets, with the data shaped to match your schema validators. The part worth keeping is the insistence on idempotency: clear-then-insert or upsert means you won't end up with duplicate rows after the third run at 11pm. It also draws a hard line against putting secrets or PII into a shared deployment, which is the right default. The main gap is that it says little about handling relationships between tables or very large imports, so you'll still need to think about ordering and batch size yourself.

skills.sh installs: 41K
GitHub stars: 69
last updated: Oct 26, 2026

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Install

$ npx -y skills add convex/agent-skills --skill convex-seed --agent claude-code

Installs into .claude/skills of the current project.

Files

Seed / import data

Populate tables via an internalMutation seed function (re-runnable) or npx convex import, matching the schema.

Workflow

For fixtures: write an internalMutation that inserts sample rows; run it with npx convex run.
For bulk import: shape the data to the schema and use npx convex import.
Make seeding idempotent (clear-then-insert or upsert) so re-running is safe.
Verify row counts.