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.
npx skills add AmariahAK/atlarix-skills --skill acr-convex-cursorrules-prompt-filegit clone --depth 1 https://github.com/AmariahAK/atlarix-skillsWrote 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/skills/amariahak/atlarix-skills/acr-convex-cursorrules-prompt-file)<a href="https://agentmods.dev/skills/amariahak/atlarix-skills/acr-convex-cursorrules-prompt-file"><img src="https://agentmods.dev/badge/skills/amariahak/atlarix-skills/acr-convex-cursorrules-prompt-file/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/skills/amariahak/atlarix-skills/acr-convex-cursorrules-prompt-file"><img src="https://agentmods.dev/badge/skills/amariahak/atlarix-skills/acr-convex-cursorrules-prompt-file.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 | $0.00009 | $0.06368 |
| Opus 5 | $0.00005 | $0.03184 |
| Sonnet 5 | $0.00002 | $0.01274 |
| Haiku 4.5 | $0.00001 | $0.00637 |
Grade A, and why
Cursor rules for Convex development with best practices 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 12d 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
91% identical to convex-rules — 512 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 — 688 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cursor rules for Convex development with best practices
When to use this skill
Cursor rules for Convex development with best practices.
Source
Synced from https://github.com/PatrickJS/awesome-cursorrules/tree/main/rules/convex-cursorrules-prompt-file.mdc.
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.
Validators
-
Below is an example of an array validator: ```typescript 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: ```typescript 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(), }), ), ) }); ``` -
Always use the
v.null()validator when returning a null value. Below is an example query that returns a null value: ```typescript import { query } from "./_generated/server"; import { v } from "convex/values";export const exampleQuery = query({ args: {}, returns: v.null(), handler: async (ctx, args) => { console.log("This query returns a null value"); return null; }, }); ``` -
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'sundefinedis not a valid Convex value. Functions the returnundefinedor do not return will returnnullwhen called from a client. Usenullinstead. | | Int64 | bigint |3n|v.int64()| Int64s only support BigInts between -2^63 and 2^63-1. Convex supportsbigints 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 asArrayBuffers. 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 "". |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 688 lines · 9 tokens per session scan A f1e8dd2ab977
Cursor rules for Convex development with best practices is a skill published in the GitHub repository AmariahAK/atlarix-skills (2 stars, last pushed 5d ago), licensed Apache-2.0. It adds 9 tokens to every session and 6,368 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to convex-rules, differing in 512 lines, and is treated as a copy.
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