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Convex backend specialist

Writes and reviews Convex backend code (schemas, queries, mutations, actions) using Convex's current conventions.

Source Download skill
Repository
openclaw/clawhub
Stars
9,546
Licence
MIT
Files
1 file

What it does

Convex is a backend platform where app logic, data storage and server functions live together. Once this skill is installed, an AI agent working on code inside a convex/ folder follows a checklist of Convex-specific rules that general AI models often get wrong, such as using object-form function definitions with argument and return validators, querying through indexes instead of full-table scans, and keeping internal functions private unless a client needs them. It also asks the agent to check that the code compiles and pushes to a Convex deployment before calling the work finished.

Great for

  • Developers building an app on Convex who want fewer deploy errors from AI-written backend code
  • Teams with an existing convex/ directory who want consistent schema, index and validator patterns
  • Developers adding LLM chat or multi-step workflows who want the agent to use the recommended Convex components

Skip it if

  • Projects that do not use Convex, since the rules are specific to its runtime and APIs and would mislead other backends
  • Production databases where the agent running npx convex dev or changing deployment config could affect live data; review commands before letting it run them
  • Users who are not comfortable with a command-line development setup, because the skill assumes Node tooling and a Convex login

Try asking

  • “Add a new table for orders with an index on userId and a query that returns a user's recent orders”
  • “Write a mutation that updates a task status and validates the status with v.union of v.literal values”
  • “Set up a daily cron job that calls an action to sync data from an external API”
  • “Add file upload storage to my Convex app and return a download URL from a query”
Step-by-step guide: how to use Convex backend specialistInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    convex-expert.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip convex-expert.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip convex-expert.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Point the agent at your existing convex/schema.ts before asking for changes so it follows your current table and index design
  • Ask it to explain the commands it wants to run (npx tsc --noEmit, npx convex dev --once) and confirm which deployment they target before approving
  • Use it on a development deployment first; the skill itself warns against switching a signed-in user to anonymous mode, so check your .env.local afterwards

What's inside

  • SKILL.md

Redistributed unmodified from openclaw/clawhub under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.