aeo-optimization

aeo-optimization is a skill for Claude Code from alinaqi/maggy. It costs 20 tokens per session (3,791 once invoked), scanned A, original, MIT.

A content-planning guide for making webpages easier for AI answer systems—such as ChatGPT, Claude, Perplexity, and Google AI Overviews—to understand and cite.

In plain words
What is it for?
Use it to plan linked facts, reusable page layouts, and groups of related content intended for AI-generated answers and citations.
Why use it?
It helps address the problem of AI systems using information from many sources without sending readers to the original webpage. It organizes content so a company can present clearer answers about its products or subject.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: positional $N argument.

not rated 705repo today A scan Socket: passSnyk: passSkillSpector: pass 20 tokens original MIT

Good fit Use it to plan linked facts, reusable page layouts, and groups of related content intended for AI-generated answers and citations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alinaqi/maggy/aeo-optimization
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.

Any agent
npx skills add alinaqi/maggy --skill aeo-optimization
Clone the repo
git clone --depth 1 https://github.com/alinaqi/maggy

Made for: Claude Code.

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 aeo-optimization

README.md
[![agentmods](https://agentmods.dev/badge/skills/alinaqi/maggy/aeo-optimization.svg)](https://agentmods.dev/skills/alinaqi/maggy/aeo-optimization)
Your own site
<a href="https://agentmods.dev/skills/alinaqi/maggy/aeo-optimization"><img src="https://agentmods.dev/badge/skills/alinaqi/maggy/aeo-optimization.svg" alt="Measured on agentmods" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,791 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 14 Jul 2026
  • Snyk pass 14 Jul 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00020 $0.03791
Opus 5 $0.00010 $0.01895
Sonnet 5 $0.00004 $0.00758
Haiku 4.5 $0.00002 $0.00379

Measured 8d ago against content hash 5a2132d22ee4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

aeo-optimization 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 8d 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.

skills/aeo-optimization/SKILL.md · 556 lines

How it starts

The opening of the file, as written. The whole thing — 556 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Engine Optimization (AEO) Skill

Purpose: Optimize content for AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) so your brand gets cited in AI-generated answers.

Source: Based on HubSpot's AEO Guide and industry best practices.


Why AEO Matters Now

┌────────────────────────────────────────────────────────────────┐
│  THE GREAT DECOUPLING                                          │
│  ────────────────────────────────────────────────────────────  │
│  Impressions ≠ Clicks anymore.                                 │
│  AI engines compile answers from multiple sources.             │
│  More buyer journey happens inside chat experiences.           │
│  58% of Google searches = zero clicks (AI overviews).          │
├────────────────────────────────────────────────────────────────┤
│  THE OPPORTUNITY                                               │
│  ────────────────────────────────────────────────────────────  │
│  Shape what AI engines say about your category and product.    │
│  Get cited as the authoritative source.                        │
│  Best answer > Best page ranking.                              │
└────────────────────────────────────────────────────────────────┘

Key Stats:

  • 70% of consumers use ChatGPT for searches
  • 47% of Google queries show AI overviews
  • Average ChatGPT prompt: 23 words (vs 4.2 for Google)
  • AEO market: $886M (2024) → $7.3B (2031)

How AI Engines Choose Answers

AI engines use three main signals to select content for answers:

1. Consensus

Facts that appear across multiple credible sources get trusted and reused.

How to build consensus:

  • Repeat key facts consistently across your own pages
  • Use same terminology as industry leaders
  • Link to and from authoritative external sources
  • Create internal content clusters that reinforce each other

2. Information Gain

Net-new insight beats generic advice. AI engines prefer content that adds value.

Read the full file on GitHub · 556 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. 8d ago First seen · 556 lines · 20 tokens per session scan A 5a2132d22ee4

Subscribe to this mod's changes

aeo-optimization is a skill published in the GitHub repository alinaqi/maggy (705 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 3,791 once invoked, about $0.0001 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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