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Ai Search Optimization

Checked
dirnbauer·vlatest·ai-ml

Helps with AI, search, optimization as part of agent workflows workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add dirnbauer/webconsulting-skills --skill ai-search-optimization -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

dirnbauer

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned dirnbauer/webconsulting-skills at 98b562d70f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
98b562d70f
Manifest
skills/ai-search-optimization/SKILL.md
Scanned
18 files, 2,580 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill, AI Search Optimization (AEO & GEO), helps optimize content for visibility within AI-powered search engines and answer engines like ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot. It focuses on strategies to ensure your content is cited as the source of answers provided by these platforms, rather than simply driving clicks to a website. The skill emphasizes structuring content to provide direct, concise answers to user queries, aligning with how generative AI platforms present information.

When to use it

  • You want your content to be featured in Google AI Overviews, Perplexity AI, ChatGPT Search, or Microsoft Copilot Search.
  • You're creating content that aims to directly answer common questions users might have.
  • You’re looking to improve visibility beyond traditional search engine rankings and target "zero-click" searches where users get answers directly from the AI platform.
  • You are optimizing for conversational, long-tail queries rather than short keywords.

Key capabilities

  • Answer Engine Optimization (AEO): Focuses on structuring content to be cited as a direct answer source in AI platforms.
  • Generative Engine Optimization (GEO): Enhances visibility within generative AI search results that synthesize information from multiple sources.
  • Content Structure Guidance: Provides recommendations for using semantic HTML structure (e.g., <article>, <header>, <h1>, <p class="summary">) to improve content readability and extractability by AI systems.
  • Target Platform Awareness: Covers strategies relevant to Google AI Overviews, Perplexity AI, ChatGPT Search, Microsoft Copilot Search, and voice assistants (Siri, Alexa, Google Assistant).

Example prompts

  • "How can I optimize this article for Google AI Overviews?"
  • "Analyze this content and suggest changes to make it more suitable for Perplexity AI."
  • “What are the key differences between traditional SEO and AEO/GEO?”
  • "Suggest a semantic HTML structure for an article answering the question: 'How does photosynthesis work?'"

Tips & gotchas

  • AEO/GEO prioritizes providing direct answers over driving website clicks, so content should be concise and easily digestible.
  • The skill focuses on strategies specifically for AI-powered platforms; traditional SEO techniques may not always apply.
  • Understanding the evolving landscape of generative AI search (e.g., Google AI Overviews) is crucial for effective optimization.