intent-ref-information-architecture

A reference for organizing navigation, categories, labels, and search paths so people can find information. Information architecture is the structure that connects content to users' mental models.

In plain words
What is it for?
Use it to design site navigation, content taxonomies, page hierarchies, search experiences, and wayfinding patterns.
Why use it?
It explains the trade-offs between findability, scalability, and cognitive effort, helping prevent confusing menus, deep hierarchies, and categories that make sense only to an organization.

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

Made for: Cursor.

Per session 38 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,120 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 $0.00038 $0.03120
Opus 5 $0.00019 $0.01560
Sonnet 5 $0.00008 $0.00624
Haiku 4.5 $0.00004 $0.00312

Measured 2d ago against content hash ee4bc583d149, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

intent-ref-information-architecture 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/intent-ref-information-architecture.mdc · 225 lines

How it starts

The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Information Architecture

Every navigation pattern is a trade-off between findability, scalability, and cognitive load. There is no universally correct pattern — there's the right pattern for your content, users, and context.

Hierarchical (Tree)

The most common pattern. Content is organized in nested categories: top-level → subcategory → item.

When it works: Large content sets with clear categorical relationships. Users have a general sense of what category their item belongs to. Content creators can maintain consistent categorization.

When it fails: When categories overlap significantly (is a "wireless mouse" in Accessories, Computers, or Peripherals?). When the hierarchy is deeper than 3-4 levels — users lose orientation quickly. When the hierarchy reflects organizational structure rather than user mental models ("Products" → "Business Unit A" → "Division 2" → "Team Alpha's Output").

Watch for: The "miscellaneous" drawer. If you have a category called "Other" or "General" that keeps growing, your hierarchy isn't working. Also: category names that mean something to the organization but nothing to users.

Hub-and-Spoke

A central hub connects to independent sections. Each section is largely self-contained. Users return to the hub to navigate between sections.

When it works: Mobile apps with distinct functional areas (Messages, Camera, Profile). Products where tasks are independent — you don't need to combine search results with your shopping cart. Kiosk interfaces and set-top boxes where the input model favors focused navigation.

When it fails: When users need to move fluidly between sections. When tasks span multiple sections. When the "hub" becomes a dumping ground for everything that doesn't fit in a spoke.

Watch for: The desire to add cross-links between spokes. Once spokes start linking to each other extensively, the hub-and-spoke model is fighting the user's actual workflow. Consider switching to a different pattern.

Read the full file on GitHub · 225 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 · 225 lines · 3,120 tokens per session scan A ee4bc583d149

Subscribe to this mod's changes

intent-ref-information-architecture is a cursor rule published in the GitHub repository ghaida/intent (142 stars, last pushed 1mo ago), licensed CC0-1.0. It adds 38 tokens to every session and 3,120 once invoked, about $0.0002 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.