localize

A guide to adapting a product for different countries and cultures, rather than translating its words alone. It covers language, writing direction, dates, colors, icons, navigation, trust signals, payments, and local expectations.

In plain words
What is it for?
Use it for international expansion, localization reviews, right-to-left languages, cultural checks, local payment flows, date formats, and testing an experience in a new market.
Why use it?
A design that works in one market may be confusing, inappropriate, or legally unsuitable in another. Planning for these differences early avoids expensive changes later.

Cursor rule for Cursor

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/ghaida/intent/localize
Clone the repo
git clone --depth 1 https://github.com/ghaida/intent

Made for: Cursor.

Per session 140 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,780 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00140 $0.03780
Opus 5 $0.00070 $0.01890
Sonnet 5 $0.00028 $0.00756
Haiku 4.5 $0.00014 $0.00378

Measured 2d ago against content hash 999012223c91, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

localize 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 2d 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/localize.mdc · 292 lines

How it starts

The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Localize — Design Across Cultures

Overview

Localization is not translation. Translation converts words; localization adapts the experience.

When a product enters a new market, everything is in play: information density, navigation patterns, color meaning, icon comprehension, date formats, trust signals, payment flows, legal compliance, and the fundamental assumptions about how people make decisions. A checkout flow designed for US consumers doesn't become a Japanese experience by translating the strings. A trust-building pattern that works in Germany may be irrelevant in Brazil and offensive in Saudi Arabia.

Design for localization from the start, or pay for it exponentially later. Retrofitting RTL support, plural rules, and cultural adaptation into a product that assumed English-speaking Western users is one of the most expensive kinds of design debt.

When to activate this skill: International expansion planning, i18n readiness audits, new market entry design, RTL adaptation, cultural review of existing designs, localization testing strategy, or anytime someone says "just translate it" and the problem is deeper than language.


Skill family

Localize works alongside the full Intent skill system:

  • /articulate: Everything they write will be localized. Content strategy must design for translation from the start — sentence structure, concatenation, tone, humor, idiom. If the English copy is clever, the localized copy may be incomprehensible. Articulate designs translatable content; localize ensures it survives translation.
  • /organize: Navigation and labeling may need cultural adaptation. Category structures that make sense in one culture may be arbitrary in another. Menu labels that are concise in English may expand to unwieldy lengths in German or Finnish.
  • /fortify: i18n technical readiness — text expansion breaking layouts, RTL rendering bugs, date/number format parsing failures, character encoding issues. Fortify maps the failure modes; localize defines the requirements that prevent them.
  • /strategize: Market analysis and audience definition per locale. Which markets, in what order, with what level of adaptation? /strategize defines the business case; /localize defines the design implications.
  • /investigate: Cultural research methods for unfamiliar markets. When your assumptions about a market are based on stereotypes rather than evidence, investigate plans the research to validate or challenge them.
  • /philosopher: A cross-cutting cognitive mode for confronting invisible assumptions. Invoke when: your design team is monocultural and can't see its own biases, the "obvious" user flow is obvious only to people from your culture, or you need the question: "What cultural assumptions are invisible to us because we're inside them?"

Read the full file on GitHub · 292 lines

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. 2d ago First seen · 292 lines · 3,780 tokens per session scan A 999012223c91

Subscribe to this mod's changes

localize is a cursor rule published in the GitHub repository ghaida/intent (139 stars, last pushed 1mo ago), licensed CC0-1.0. It adds 140 tokens to every session and 3,780 once invoked, about $0.0007 per session on Opus 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 2026-08-30.