1002-rails-models

1002-rails-models is a cursor rule for coding agents from verygoodplugins/ai-editor-rules. It costs 0 tokens per session (727 once invoked), scanned A, original, GPL-3.0.

A set of rules for Rails 7.2 models, the code that represents and validates application data. Rails is a Ruby web framework.

In plain words
What is it for?
Use it when creating or modifying Rails 7.2 models.
Why use it?
It keeps model changes aligned with the project's expected Rails patterns and standards.

Cursor rule

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.

agentmods
npx agentmods add rules/verygoodplugins/ai-editor-rules/1002-rails-models
Clone the repo
git clone --depth 1 https://github.com/verygoodplugins/ai-editor-rules

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 1002-rails-models

README.md
[![agentmods](https://agentmods.dev/badge/rules/verygoodplugins/ai-editor-rules/1002-rails-models.svg)](https://agentmods.dev/rules/verygoodplugins/ai-editor-rules/1002-rails-models)
Your own site
<a href="https://agentmods.dev/rules/verygoodplugins/ai-editor-rules/1002-rails-models"><img src="https://agentmods.dev/badge/rules/verygoodplugins/ai-editor-rules/1002-rails-models.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 727 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00000 $0.00727
Opus 5 $0.00000 $0.00364
Sonnet 5 $0.00000 $0.00145
Haiku 4.5 $0.00000 $0.00073

Measured 3d ago against content hash 1e95512a17b4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

1002-rails-models 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 3d 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/rails/rules/1002-rails-models.mdc · 108 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 3d ago First seen · 108 lines · 0 tokens per session scan A 1e95512a17b4

Subscribe to this mod's changes

1002-rails-models is a cursor rule published in the GitHub repository verygoodplugins/ai-editor-rules (2 stars, last pushed 1y ago), licensed GPL-3.0. It costs nothing until one of its globs matches a file; then it loads 727 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 2026-08-31.