convex_rules

convex_rules is a cursor rule for Cursor from HomenShum/NodeBenchAI. It costs 4,645 tokens per session, scanned A, original, MIT.

Development rules and examples for Convex projects. Convex is a backend platform for databases, server functions, and HTTP endpoints.

In plain words
What is it for?
Use them when building or reviewing Convex database tables, queries, mutations, validators, and HTTP routes.
Why use it?
They provide consistent patterns for defining database schemas, validating data, handling requests, and writing backend functions. This helps avoid incorrect Convex-specific code.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

Good fit Use them when building or reviewing Convex database tables, queries, mutations, validators, and HTTP routes.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/homenshum/nodebenchai/convex_rules
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/HomenShum/NodeBenchAI

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for convex_rules

README.md
[![agentmods](https://agentmods.dev/badge/rules/homenshum/nodebenchai/convex_rules/github.svg)](https://agentmods.dev/rules/homenshum/nodebenchai/convex_rules)
Your own site
<a href="https://agentmods.dev/rules/homenshum/nodebenchai/convex_rules"><img src="https://agentmods.dev/badge/rules/homenshum/nodebenchai/convex_rules/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for convex_rules

Your own site · 80×15
<a href="https://agentmods.dev/rules/homenshum/nodebenchai/convex_rules"><img src="https://agentmods.dev/badge/rules/homenshum/nodebenchai/convex_rules.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 4,645 This file is loaded in full into every session.
When invoked 4,645 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.04645 $0.04645
Opus 5.5 $0.01858 $0.01858
Sonnet 5.5 $0.00929 $0.00929
Haiku 4.5 $0.00464 $0.00464

Measured 1mo ago against content hash 1630409c6140, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

convex_rules scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/convex_rules.mdc · 371 lines

How it starts

The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Convex guidelines

Function guidelines

Http endpoint syntax

  • HTTP endpoints are defined in convex/http.ts and require an httpAction decorator. For example:
import { httpRouter } from "convex/server";
import { httpAction } from "./_generated/server";
const http = httpRouter();
http.route({
  path: "/echo",
  method: "POST",
  handler: httpAction(async (ctx, req) => {
    const body = await req.bytes();
    return new Response(body, { status: 200 });
  }),
});
  • HTTP endpoints are always registered at the exact path you specify in the path field. For example, if you specify /api/someRoute, the endpoint will be registered at /api/someRoute.

Validators

  • Below is an example of an array validator:
import { mutation } from "./_generated/server";
import { v } from "convex/values";

export default mutation({
  args: {
    simpleArray: v.array(v.union(v.string(), v.number())),
  },
  handler: async (ctx, args) => {
    //...
  },
});
  • Below is an example of a schema with validators that codify a discriminated union type:
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  results: defineTable(
    v.union(
      v.object({
        kind: v.literal("error"),
        errorMessage: v.string(),
      }),
      v.object({
        kind: v.literal("success"),
        value: v.number(),
      }),
    ),
  ),
});
  • Here are the valid Convex types along with their respective validators:
    Convex Type TS/JS type Example Usage Validator for argument validation and schemas Notes
    Id string doc._id v.id(tableName)
    Null null null v.null() JavaScript's undefined is not a valid Convex value. Functions the return undefined or do not return will return null when called from a client. Use null instead.
    Int64 bigint 3n v.int64() Int64s only support BigInts between -2^63 and 2^63-1. Convex supports bigints in most modern browsers.
    Float64 number 3.1 v.number() Convex supports all IEEE-754 double-precision floating point numbers (such as NaNs). Inf and NaN are JSON serialized as strings.
    Boolean boolean true v.boolean()
    String string "abc" v.string() Strings are stored as UTF-8 and must be valid Unicode sequences. Strings must be smaller than the 1MB total size limit when encoded as UTF-8.
    Bytes ArrayBuffer new ArrayBuffer(8) v.bytes() Convex supports first class bytestrings, passed in as ArrayBuffers. Bytestrings must be smaller than the 1MB total size limit for Convex types.
    Array Array [1, 3.2, "abc"] v.array(values) Arrays can have at most 8192 values.
    Object Object {a: "abc"} v.object({property: value}) Convex only supports "plain old JavaScript objects" (objects that do not have a custom prototype). Objects can have at most 1024 entries. Field names must be nonempty and not start with "$" or "_".

| Record | Record | {"a": "1", "b": "2"} | v.record(keys, values) | Records are objects at runtime, but can have dynamic keys. Keys must be only ASCII characters, nonempty, and not start with "$" or "_". |

Read the full file on GitHub · 371 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 371 lines · 4,645 tokens per session scan A 1630409c6140

Subscribe to this mod's changes

convex_rules is a cursor rule published in the GitHub repository HomenShum/NodeBenchAI (15 stars, last pushed today), licensed MIT. It adds 4,645 tokens to every session, about $0.0186 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.