geo-content-optimizer_skill

This skill optimizes content for both SEO and AI readability, organizing structure to boost Google indexing and enhance AI model citation.
  • Python

15

GitHub Stars

1

Bundled Files

3 weeks ago

Catalog Refreshed

2 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstart where the catalogue uses aiagentskills.

npx veilstart add skill yangliu2060/smith--skills --skill geo-content-optimizer

  • SKILL.md5.9 KB

Overview

This skill optimizes content for both search engines (SEO) and large language models (GEO) so articles get indexed by Google and are more likely to be cited by AI like ChatGPT or Claude. It restructures text, refines metadata, and produces an actionable report with suggested edits and ready-to-use, AI-friendly excerpts. The goal is higher discoverability and clearer, citation-ready knowledge for generative engines.

How this skill works

The skill accepts plain text, Markdown, or a webpage URL and runs a two-stage analysis: SEO checks (titles, meta description, headings, technical signals) and GEO checks (structured facts, citation-friendly sentences, knowledge density). It produces an optimized version of the content, a checklist of applied changes, keyword suggestions, and a short list of sentences most likely to be quoted by LLMs. Results are saved in timestamped files for tracking and reuse.

When to use it

  • Preparing blog posts or articles for both Google ranking and AI citation
  • Converting existing pages into clear, structured knowledge for LLMs
  • Creating marketing or help content that should be directly quotable by AI assistants
  • Auditing content before publication to improve readability and factual density
  • Batch-optimizing multiple pages for consistent SEO + GEO signals

Best practices

  • Start each section with a clear, single-sentence conclusion that can be quoted
  • Use hierarchical headings (H1 > H2 > H3) and numbered lists for procedural content
  • Keep paragraphs short (2–4 sentences) and include one core idea per paragraph
  • Add concrete data, authority sources, and inline citations where possible
  • Maintain keyword focus (1–2% density) while avoiding keyword stuffing

Example use cases

  • Optimize a how-to blog post so search engines index it and LLMs extract step summaries
  • Refactor product documentation into concise facts and numbered procedures for AI assistants
  • Improve landing page copy with an SEO-friendly title and GEO-ready lead sentences
  • Turn research notes into an article with clear, quotable conclusions and cited sources
  • Batch-process a site to produce JSON reports for content auditing and A/B testing

FAQ

Plain text, Markdown, or a webpage URL (the skill can fetch page content).

Will this guarantee higher search rankings or AI citations?

No guarantee; it improves signals and citation-friendliness, but outcomes depend on search/AI algorithms and competition.

What outputs do I get?

An optimized content file, a detailed optimization report, a checklist of changes, suggested keywords, and top quoteable sentences.

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