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.
git clone --depth 1 https://github.com/waynesutton/promptstackWrote 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.
[](https://agentmods.dev/rules/waynesutton/promptstack/convex)<a href="https://agentmods.dev/rules/waynesutton/promptstack/convex"><img src="https://agentmods.dev/badge/rules/waynesutton/promptstack/convex/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.
<a href="https://agentmods.dev/rules/waynesutton/promptstack/convex"><img src="https://agentmods.dev/badge/rules/waynesutton/promptstack/convex.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.04157 |
| Opus 5.5 | $0.00000 | $0.01663 |
| Sonnet 5.5 | $0.00000 | $0.00831 |
| Haiku 4.5 | $0.00000 | $0.00416 |
Grade A, and why
convex 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- convexrules — 94% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 498 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convex guidelines
Function guidelines
New function syntax
- ALWAYS use the new function syntax for Convex functions. For example:
typescript import { query } from "./_generated/server"; import { v } from "convex/values"; export const f = query({ args: {}, returns: v.null(), handler: async (ctx, args) => { // Function body }, });
Http endpoint syntax
- HTTP endpoints are defined in
convex/http.tsand require anhttpActiondecorator. For example:typescript 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 }); }), });
Function registration
- Use
internalQuery,internalMutation, andinternalActionto register internal functions. These functions are private and aren't part of an app's API. They can only be called by other Convex functions. - Use
query,mutation, andactionto register public functions. These functions are part of the public API and are exposed to the public Internet. Do NOT usequery,mutation, oractionto register sensitive internal functions that should be kept private. - You CANNOT register a function through the
apiorinternalobjects. - ALWAYS include argument and return validators for all Convex functions. If a function doesn't return anything, include
returns: v.null()as its output validator. - If the JavaScript implementation of a Convex function doesn't have a return value, it implicitly returns
null.
Function calling
-
Use
ctx.runQueryto call a query from a query, mutation, or action. -
Use
ctx.runMutationto call a mutation from a mutation or action. -
Use
ctx.runActionto call an action from an action. -
ONLY call an action from another action if you need to cross runtimes (e.g. from V8 to Node). Otherwise, pull out the shared code into a helper async function and call that directly instead.
-
Try to use as few calls from actions to queries and mutations as possible. Queries and mutations are transactions, so splitting logic up into multiple calls introduces the risk of race conditions.
-
All of these calls take in a
FunctionReference. Do NOT try to pass the callee function directly into one of these calls. -
When using
ctx.runQuery,ctx.runMutation, orctx.runActionto call a function in the same file, specify a type annotation on the return value to work around TypeScript circularity limitations. For example, ``` export const f = query({ args: { name: v.string() }, returns: v.string(), handler: async (ctx, args) => { return "Hello " + args.name; }, });export const g = query({ args: {}, returns: v.null(), handler: async (ctx, args) => { const result: string = await ctx.runQuery(api.example.f, { name: "Bob" }); return null; }, }); ```
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.
- 1mo ago First seen · 498 lines · 0 tokens per session scan A 684ba426232a
convex is a cursor rule published in the GitHub repository waynesutton/promptstack (78 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,157 tokens. 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.
Other cursor rules, from other repositories
supabase
Do not use the Supabase Client, instead use the Jawn Client and put all new endpoints in controllers. Don't use RLS policies, instead enable RLS for new tables and revoke privledges. Example.
jawn
Cursor rule "jawn" from Helicone/helicone, covering helicone jawn controller and tanstack query integration, controller pattern, manager pattern, frontend hooks with tanstack query and type definitions.
rulesforconvex
description: Convex guidelines globs: alwaysApply: true.
startup-migration-bounded-work
Production djangostartup migrate must be bounded; never run makemigrations in production.
redis_rate_limiting
Complete guide for implementing Redis-based rate limiting with authentication troubleshooting and FastAPI integration.
schema
Scalable and secure schema design patterns for relational databases, NoSQL, and APIs. / TR: İlişkisel veri tabanları, NoSQL ve API'ler için ölçeklenebilir ve güvenli şema tasarım kalıpları.