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.
npx skills add textura-agency/next16-claude-starter --skill aeo-visibilitygit clone --depth 1 https://github.com/textura-agency/next16-claude-starterWrote 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/skills/textura-agency/next16-claude-starter/aeo-visibility)<a href="https://agentmods.dev/skills/textura-agency/next16-claude-starter/aeo-visibility"><img src="https://agentmods.dev/badge/skills/textura-agency/next16-claude-starter/aeo-visibility/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/skills/textura-agency/next16-claude-starter/aeo-visibility"><img src="https://agentmods.dev/badge/skills/textura-agency/next16-claude-starter/aeo-visibility.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00098 | $0.01088 |
| Opus 5 | $0.00049 | $0.00544 |
| Sonnet 5 | $0.00020 | $0.00218 |
| Haiku 4.5 | $0.00010 | $0.00109 |
Grade A, and why
aeo-visibility 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 12d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AEO — being citable, not just rankable
Classic SEO gets you ranked. AEO gets you quoted. The mechanics differ: answer engines extract self-contained claims from crawlable text, and they weight consistency of facts about an entity across the whole web.
1. Let the crawlers in — deliberately
src/app/robots.tsdecides this. Answer-engine crawlers includeGPTBot,OAI-SearchBot,ChatGPT-User,ClaudeBot,Claude-SearchBot,PerplexityBot,Google-Extended,CCBot,Bytespider.- Ask the user before changing this. "Be cited by AI" and "don't train on my
content" are different goals with different bots: training crawlers
(
GPTBot,ClaudeBot,CCBot,Google-Extended) versus live search/citation crawlers (OAI-SearchBot,Claude-SearchBot,PerplexityBot). Blocking the training set while allowing the search set is a coherent position; blocking everything and expecting citations is not. - Verify server-side rendering: answer-engine crawlers are far less reliable at executing JavaScript than Googlebot. Anything client-rendered may be invisible to them. In this starter, content is server-rendered and animations only animate — keep it that way.
2. llms.txt
A plain-markdown map of the site at /llms.txt for language models. Serve it
from src/app/llms.txt/route.ts (a Route Handler returning text/plain) so it
stays in sync with real routes rather than rotting as a static file.
# <Site name>
> One-sentence description of what the company does and for whom.
## Core pages
- [Services](https://example.com/services): what is offered, to whom
- [About](https://example.com/about): who the company is, founded, location
## Key facts
- Founded: 2019 · HQ: Berlin · Focus: <specifics>
Keep it factual and short. It is a summary for a machine, not a marketing page.
3. Structure content so it can be extracted
- Answer first. Lead each section with the direct claim in one or two sentences, then support it. Content that builds to a conclusion gets skipped.
- One idea per heading, and phrase headings as the questions people ask.
- Self-contained sentences. "Our approach is faster" is unusable out of context; "Textura ships marketing sites in four weeks" survives extraction.
- Concrete specifics — numbers, dates, named methods, prices where possible. Vague marketing language is unquotable.
- Comparison and definition content punches above its weight: "X vs Y", "What is X", pricing pages, and genuine FAQs.
- Mark FAQs up with
FAQPage(see theschema-markupskill).
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.
- 12d ago First seen · 89 lines · 98 tokens per session scan A 2ff28b490558
aeo-visibility is a skill published in the GitHub repository textura-agency/next16-claude-starter (117 stars, last pushed 4d ago), licensed Unlicense. It adds 98 tokens to every session and 1,088 once invoked, about $0.0005 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.
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