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.
git clone --depth 1 https://github.com/ghaida/intentWrote 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/rules/ghaida/intent/intent-ref-information-architecture)<a href="https://agentmods.dev/rules/ghaida/intent/intent-ref-information-architecture"><img src="https://agentmods.dev/badge/rules/ghaida/intent/intent-ref-information-architecture/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/rules/ghaida/intent/intent-ref-information-architecture"><img src="https://agentmods.dev/badge/rules/ghaida/intent/intent-ref-information-architecture.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 | $0.03120 | $0.03120 |
| Opus 5.5 | $0.01248 | $0.01248 |
| Sonnet 5.5 | $0.00624 | $0.00624 |
| Haiku 4.5 | $0.00312 | $0.00312 |
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 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.
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
Navigation Patterns
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.
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.
- 1mo ago First seen · 225 lines · 3,120 tokens per session scan A ee4bc583d149
intent-ref-information-architecture is a cursor rule published in the GitHub repository ghaida/intent (214 stars, last pushed 7d ago), licensed CC0-1.0. It adds 3,120 tokens to every session, about $0.0125 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 2026-08-30.
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