convex-seed
A skill for seeding or bulk-importing data into a Convex database, using a re-runnable internalMutation seed function or `npx convex import` while matching the schema validators. It makes data initialization idempotent and verifiable across dev, preview, and demo deployments, so re-running seeds is safe and never pollutes shared environments with duplicates or secrets.
npx skills add https://github.com/convex/agent-skills --skill convex-seedBefore / After Comparison
2 组Developers hand-write one-off insert scripts whose fields often mismatch the schema validators, then iterate on errors; re-running duplicates rows and forces manual table wipes.
This Skill seeds via a re-runnable internalMutation or `npx convex import`, matching validators exactly with clear-then-insert or upsert semantics, so re-running is safe.
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.
Rules
- Seed via internalMutation or convex import, matching validators.
- Make seeding idempotent.
- Never seed secrets/PII into a shared deployment.
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