domain-modeling

domain-modeling is a cursor rule for Cursor from BetterTyped/hype-stack. It costs 355 tokens per session, scanned A, original, MIT.

A set of rules for using consistent terms in a software project and recording architecture decisions.

In plain words
What is it for?
It helps teams define shared vocabulary and write architecture decision records, which document why a system was designed in a particular way.
Why use it?
It reduces confusion about domain language and preserves the reasons behind important design choices.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

Good fit It helps teams define shared vocabulary and write architecture decision records, which document why a system was designed in a particular way.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/bettertyped/hype-stack/domain-modeling
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/BetterTyped/hype-stack

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 domain-modeling

README.md
[![agentmods](https://agentmods.dev/badge/rules/bettertyped/hype-stack/domain-modeling/github.svg)](https://agentmods.dev/rules/bettertyped/hype-stack/domain-modeling)
Your own site
<a href="https://agentmods.dev/rules/bettertyped/hype-stack/domain-modeling"><img src="https://agentmods.dev/badge/rules/bettertyped/hype-stack/domain-modeling/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 domain-modeling

Your own site · 80×15
<a href="https://agentmods.dev/rules/bettertyped/hype-stack/domain-modeling"><img src="https://agentmods.dev/badge/rules/bettertyped/hype-stack/domain-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 355 This file is loaded in full into every session.
When invoked 355 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 $0.00355 $0.00355
Opus 5.5 $0.00142 $0.00142
Sonnet 5.5 $0.00071 $0.00071
Haiku 4.5 $0.00036 $0.00036

Measured 1mo ago against content hash 998455bbac7d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

domain-modeling 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/domain-modeling.mdc · 25 lines

What it actually says

Domain Vocabulary and Decisions

Glossary (CONTEXT.md)

Canonical domain terms live in CONTEXT.md at the repo root. Consistent vocabulary is what keeps schemas, routes, types, and UI copy coherent across sessions.

  • Use glossary terms exactly — in code, schemas, route paths, DB tables, and messages. Do not invent synonyms (account vs user vs member, cancel vs revoke — pick the canonical one).
  • When you introduce a new domain concept, add it to CONTEXT.md in the same change: one line, term + definition.
  • When the user's wording conflicts with the glossary, point out the conflict and ask which term wins — then update the glossary if it changes.
  • If CONTEXT.md does not exist yet, create it the first time a domain term needs pinning down.

Architecture Decision Records (docs/adr/)

Significant architectural decisions get a short ADR in docs/adr/NNNN-<slug>.md: context, decision, consequences — a few paragraphs, not an essay.

  • Read existing ADRs before proposing structural changes in the area you're touching.
  • Do not re-litigate recorded decisions. If a decision looks wrong, say so and ask — never silently refactor around it.
  • Record a new ADR when a decision is hard to reverse, cross-cutting, or the kind of thing a future session would otherwise "helpfully" undo (library choice, data model shape, seam placement).
  • Create docs/adr/ lazily, when the first ADR is needed.
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 · 25 lines · 355 tokens per session scan A 998455bbac7d

Subscribe to this mod's changes

domain-modeling is a cursor rule published in the GitHub repository BetterTyped/hype-stack (12 stars, last pushed 15d ago), licensed MIT. It adds 355 tokens to every session, about $0.0014 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 2026-08-31.