ClaudeSuperPower
SubmitLog in

seed

Skill

Seed the Convex database with starter/fixture data or import an existing dataset (CSV/JSON). TRIGGER when the user wants sample/seed data or to import a dataset into Convex. Idempotent, schema-matching.

0Machine Learning

Install

git clone https://github.com/get-convex/convex-backend-skill.git ~/.claude/skills/seed

What is seed?

Seed the Convex database with starter/fixture data or import an existing dataset (CSV/JSON). TRIGGER when the user wants sample/seed data or to import a dataset into Convex. Idempotent, schema-matching.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~51 tokens of context used while enabled, before you invoke anything

Documentation

README · ~1 min read

Seed / import data

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

Steps

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

Rules

  • Seed via internalMutation or convex import, matching validators.
  • Make seeding idempotent.
  • Never seed secrets/PII into a shared deployment.

Reviews

Log in to leave a review.

No reviews yet — be the first.

Explore related

Other things in this space — across every part of the ecosystem, not just skills.

Skillssimilar to this one

All skills →

create-atomic-tool

Build a `BaseTool[InSchema, OutSchema]` subclass — input/output schemas, `BaseToolConfig`, `run()` (and optional `run_async()`), env-driven secrets, typed failure outputs. Use when the user asks to "add a tool", "create a tool", "wrap an API as a tool", "build a `BaseTool`", "make a calculator/searc

6.1K stars

create-atomic-context-provider

Build a `BaseDynamicContextProvider` that injects a named, titled block into an agent's system prompt at every `run()` — current time, user identity, retrieved RAG docs, session state, cached DB schema. Use when the user asks to "add a context provider", "inject X into the prompt", "give the agent d

6.1K stars

framework

Guide for the Atomic Agents Python framework — schemas, agents, tools, context providers, prompts, orchestration, and provider configuration. Use when code imports from `atomic_agents`, defines an `AtomicAgent`, `BaseTool`, or `BaseIOSchema`, or the user asks about multi-agent orchestration or LLM-p

6.1K stars

Plugins

All plugins →

receipts

A personal Claude Code impact report for justifying your usage to a manager or a self-review: what you shipped, which projects it went to, and each project's share of your usage. Reads your ~/.claude/projects transcripts and runs read-only git locally; only counts and project names are sent to write

32.8K stars

atomic-agents

Comprehensive development workflow for building AI agents with the Atomic Agents framework. Includes specialized agents for schema design, architecture planning, code review, and tool development. Features guided workflows, progressive-disclosure skills, and best practice validation.

6.1K stars

databases-on-aws

Expert database guidance for the AWS database portfolio. Design schemas, execute queries, handle migrations, and choose the right database for your workload.

844 stars