# Convex Performance Audit

Audits Convex performance for reads, subscriptions, write contention, and function limits.

- Repository: https://github.com/openclaw/clawhub (9543 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add openclaw/clawhub --skill convex-performance-audit -g -a claude-code -y`
Codex: `npx skills add openclaw/clawhub --skill convex-performance-audit -g -a codex -y`
Cursor: `npx skills add openclaw/clawhub --skill convex-performance-audit -g -a cursor -y`
Gemini CLI: `npx skills add openclaw/clawhub --skill convex-performance-audit -g -a gemini-cli -y`

## Description

Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Convex Performance Audit

Diagnose and fix performance problems in Convex applications, one problem class
at a time.

## When to Use

- A Convex page or feature feels slow or expensive
- `npx convex insights --details` reports high bytes read, documents read, or
  OCC conflicts
- Low-freshness read paths are using reactivity where point-in-time reads would
  do
- OCC conflict errors or excessive mutation retries
- High subscription count or slow UI updates
- Functions approaching execution or transaction limits
- The same performance pattern needs fixing across sibling functions

## When Not to Use

- Initial Convex setup, auth setup, or component extraction
- Pure schema migrations with no performance goal
- One-off micro-optimizations without a user-visible or deployment-visible
  problem

## Guardrails

- Prefer simpler code when scale is small, traffic is modest, or the available
  signals are weak
- Do not recommend digest tables, document splitting, fetch-strategy changes, or
  migration-heavy rollouts unless there is a measured signal, a clearly
  unbounded path, or a known hot read/write path
- In Convex, a simple scan on a small table is often acceptable. Do not invent
  structural work just because a pattern is not ideal at large scale

## First Step: Gather Signals

Start with the strongest signal available:

The rest: https://github.com/openclaw/clawhub/blob/HEAD/.agents/skills/convex-performance-audit/SKILL.md