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/convexrules)<a href="https://agentmods.dev/rules/waynesutton/promptstack/convexrules"><img src="https://agentmods.dev/badge/rules/waynesutton/promptstack/convexrules/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/convexrules"><img src="https://agentmods.dev/badge/rules/waynesutton/promptstack/convexrules.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 | $0.04241 |
| Opus 5.5 | $0.00000 | $0.01696 |
| Sonnet 5.5 | $0.00000 | $0.00848 |
| Haiku 4.5 | $0.00000 | $0.00424 |
Grade A, and why
convexrules 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.
This is a copy
94% identical to convex — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 504 lines — stays where its author put it; the contents beside it link to each section on GitHub.
description: Guidelines and best practices for building Convex projects, including database schema design, queries, mutations, and real-world examples globs: **/*.{ts,tsx,js,jsx}
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 }); }), }); - HTTP endpoints are always registered at the exact path you specify in the
pathfield. For example, if you specify/api/someRoute, the endpoint will be registered at/api/someRoute.
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.
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 · 504 lines · 0 tokens per session scan A f8487418a198
convexrules 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 4,241 tokens. A static security scan graded it A with 0 findings. It is 94% identical to convex, differing in 6 lines, and is treated as a copy.
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.