convex

Set up a project with two deployments, dev (break anything) and prod (real users), and never point local dev at prod data:

npx convex login                 # the user approves in the browser, or run the setup-convex skill
npx convex dev --once            # creates the project + dev deployment, writes .env.local
npx convex env set KEY value     # server secrets (dev); add --prod for production
npx convex deploy                # production deploy

Write every function so it is safe and cheap:

• Every public query, mutation and action is callable by anyone who has the deployment URL. Check the user (ctx.auth or the Better Auth helper) and ownership inside each one; use internalQuery/internalMutation for anything only the server calls.
• Validate every argument with v.* validators.
• Read with .withIndex(...) on a selective index, never .filter on a large table. Define the index in schema.ts for each access pattern (by_userId, by_courseId_order, ...).
• Bound reads: .take(n) or .paginate() before enriching rows; never .collect() a table that grows.
• Return only the fields the client needs.
• Secrets live in Convex env vars, never in client code.

To optimize, start from live evidence:

npx convex insights --prod --details

Extract function name, warning type, per-table docs/bytes, and whether it failed or only neared a limit. Prioritize high Documents Read with low Documents Returned.

Map each hot export to convex/** and its client callsites, then diagnose before patching:

• .filter / .collect without a selective .withIndex, or an index that narrows only by tenant and still scans thousands of rows;
• per-row related fetches (N+1); recount helpers on hot mutations;
• jobs or crons that scan every row on every run;
• concurrent patches on the same document (OCC conflicts).

Apply the smallest change: add the index used by the query; .take/paginate before enrichment; denormalize list previews and fetch full rows only on detail; incremental counters instead of full recounts; cursor + per-run limit for jobs; skip no-op patches and merge same-document writes; move high-churn state to a narrower table.

Verify with the project's typecheck, tests and build, plus npx convex codegen. Re-run insights after deploy and report: hot functions, root cause, change, expected read/byte/OCC impact, validation.