Seed or import data into a Convex database using internal mutations or bulk import.
npx skills add https://github.com/openclaw/clawhub --skill convex-seed
Please help me install this Agent Skill. Skill: convex-seed Source: https://github.com/openclaw/clawhub/tree/main/.agents/skills/convex-seed Command: npx skills add https://github.com/openclaw/clawhub --skill convex-seed
Populating a Convex database with initial or test data is error-prone when done manually, and re-running seed scripts can create duplicates or schema mismatches. This Skill provides a repeatable, schema-safe workflow for seeding tables.
npx convex run.npx convex import.Seed my Convex database with sample fixture data using an idempotent internal mutation and verify the row counts.
High-intent search queries and answers about installing and using this skill.
Write an internalMutation that inserts sample rows matching your schema validators, then run it with npx convex run. For larger datasets, shape the data to the schema and use npx convex import instead.
Use a clear-then-insert or upsert pattern inside the seed mutation so re-running it does not create duplicates. After seeding, verify row counts to confirm the operation succeeded.
Use npx convex import for bulk data loading when you have a large dataset already shaped to match the schema. Use an internalMutation seed function for smaller fixture sets that need programmatic logic.
No. Never seed secrets or PII into a shared deployment. Seed data should be synthetic fixtures only, keeping sensitive values out of any environment accessible to multiple developers.
Seed inserts fail when the data does not match the schema validators defined for the table. Check that every field type and required property in your fixture rows conforms to the schema before running the mutation.
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