GEO-First SEO Audit Tool
zubair-trabzada/geo-seo-claude
Audits a website for AI search visibility across ChatGPT, Claude, Perplexity and Google AI Overviews while checking traditional SEO, schema and E-E-A-T content quality.
Makes a page or site easier for AI answer engines to find, understand, trust and quote, using metadata, structured data, an llms.txt file and clear page structure.
Install Generative Engine Optimization
$ npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tech-leads-club/agent-skills tlc-generative-engine-optimization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/tech-leads-club/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization' .claude/skills/tlc-generative-engine-optimization && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "tlc-generative-engine-optimization" agent skill from https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization into .claude/skills/tlc-generative-engine-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tlc-generative-engine-optimization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tech-leads-club/agent-skills tlc-generative-engine-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tech-leads-club/agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization' .agents/skills/tlc-generative-engine-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tlc-generative-engine-optimization" agent skill from https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization into .agents/skills/tlc-generative-engine-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tlc-generative-engine-optimization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tech-leads-club/agent-skills tlc-generative-engine-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tech-leads-club/agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization' .cursor/skills/tlc-generative-engine-optimization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "tlc-generative-engine-optimization" agent skill from https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization into .cursor/skills/tlc-generative-engine-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tlc-generative-engine-optimization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/tech-leads-club/agent-skills.git --path 'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization'--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tech-leads-club/agent-skills tlc-generative-engine-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tech-leads-club/agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization' .gemini/skills/tlc-generative-engine-optimization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "tlc-generative-engine-optimization" agent skill from https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization into .gemini/skills/tlc-generative-engine-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tlc-generative-engine-optimization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install tech-leads-club/agent-skills tlc-generative-engine-optimizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tech-leads-club/agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization' .github/skills/tlc-generative-engine-optimization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "tlc-generative-engine-optimization" agent skill from https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization into .github/skills/tlc-generative-engine-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tlc-generative-engine-optimization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tech-leads-club/agent-skills tlc-generative-engine-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tech-leads-club/agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization' .opencode/skills/tlc-generative-engine-optimization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "tlc-generative-engine-optimization" agent skill from https://github.com/tech-leads-club/agent-skills/tree/main/packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization into .opencode/skills/tlc-generative-engine-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tlc-generative-engine-optimization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
tlc-generative-engine-optimization- GitHub stars
- 7k
- Token cost
- ~2.5k tokens
- SKILL.md length
- 982 words
- Files
- 9 (incl. references)
- Skills in repo
- 74
- Repo updated
- First seen
- Licence
- MIT
At a glance
Makes a page or site easier for AI answer engines to find, understand, trust and quote, using metadata, structured data, an llms.txt file and clear page structure.
- Works in 7 steps: Plan page structure: one topic, one H1,… → Apply templates/page-metadata.html… → Add templates/techarticle.jsonld (or… → …
- Preparing a page that AI answer engines can parse and quote
- SKILL.md covers Philosophy, When to use / not use, The Six GEO Pillars and Operating Modes, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
The skill treats GEO as documentation quality rather than a trick: correct metadata, honest structured data, clear prose and stable URLs. It tells the agent never to promise rankings or AI citations, since those are decisions the engines make. The scope is technical and page-level work, and content strategy, keyword ranking, accessibility and broad site audits are sent to other skills.
Work is organized around six pillars: discoverable, understandable, useful, trustworthy, quotable and fresh. Checks include robots.txt allowing AI crawlers, one topic per page, content in static HTML, visible author and dates, a short answer before the detail, and dateModified in JSON-LD. A create mode plans page structure and applies shipped templates for page metadata, TechArticle and FAQPage JSON-LD, llms.txt, an AI-crawler robots file and a quotable article outline. The description also covers auditing or improving an existing codebase.
When your agent uses it
- Preparing a page that AI answer engines can parse and quote
- Writing an llms.txt file for a site
- Adding FAQ or article structured data to a page for AI answers
- Auditing a codebase for generative search readiness
Example prompts
- “Optimize our pricing page for AI answer engines and add the JSON-LD it needs.”
- “Write an llms.txt for our documentation site.”
- “Audit this repo for GEO and list anything that blocks AI crawlers.”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Plan page structure: one topic, one H1, question-based H2s/H3s.
- Apply templates/page-metadata.html (canonical, hreflang, meta description).
- Add templates/techarticle.jsonld (or faqpage.jsonld for FAQ pages).
- Write content in the quotable outline pattern (templates/quotable-article-outline.md): short direct answer → supporting detail → sources.
- Update robots.txt to allow AI crawlers (templates/robots-ai-crawlers.txt).
- Add or update llms.txt if the site wants to guide AI agents (templates/llms.txt).
- Run the GEO page checklist (in references/pillars-and-workflow.md).
What it can do on your machine
Read from SKILL.md and the folder at commit 120b676. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Generative Engine Optimization loads about 2.5k tokens when it runs, and up to ~5.3k if it reads all its reference files. Until then it costs about 218 tokens; SKILL.md has 982 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from tech-leads-club/agent-skills at commit 120b676, republished under its MIT licence (© tech-leads-club). 982 words, ~2,521 tokens.
Download SKILL.mdSave it as
.claude/skills/tlc-generative-engine-optimization/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- tlc-generative-engine-optimization
- description
- Generative Engine Optimization (GEO) specialist — the technical, on-page publishing work that makes a given page or site discoverable, understandable, trustworthy, quotable, and fresh for AI answer engines (Google AI Overviews, ChatGPT Search, Bing Copilot, Perplexity). Use when asked to 'optimize this page/site for GEO', 'optimize for AI search / answer engines', 'get my page cited by ChatGPT/Perplexity', 'improve AI visibility/citability', 'write an llms.txt', 'add citation-ready structure or schema for AI answers', 'otimizar para busca com IA', or to audit/create/improve a codebase for generative search. Do NOT use for AI-driven SEO content strategy or programmatic pages at scale (use ai-seo), classic keyword/SERP ranking (use seo), accessibility (use web-accessibility), or multi-area site audits (use web-quality-audit).
- metadata.version
- 1.0.0
- metadata.author
- Fernando Paladini - github.com/paladini
- license
- MIT
GEO Specialist
Expert in Generative Engine Optimization — making pages discoverable, understandable, trustworthy, quotable, and fresh for AI answer engines.
Philosophy
Treat GEO as documentation quality, not a trick. AI engines cite pages they can parse, trust, and quote. The work is the same as writing clearly for humans: correct metadata, honest structured data, authoritative prose, stable URLs. Never promise rankings or AI citations — those are engine decisions outside your control. Do the technical work well; citations follow as a byproduct.
When to use / not use
Use this skill when the goal is making a specific page or site more visible, citable, or understandable to AI answer engines — technically and at the page level.
Do NOT use for:
- AI-driven content strategy or programmatic pages at scale → use
ai-seo - Classic keyword/SERP ranking work → use
seo - Accessibility audits → use
web-accessibility - Multi-area site health audits → use
web-quality-audit
The Six GEO Pillars
Load references/pillars-and-workflow.md for the full deep-dive. Summary:
| # | Pillar | Core check |
|---|---|---|
| 1 | Discoverable | robots.txt allows AI crawlers; sitemap exists; canonical tags correct; HTTPS |
| 2 | Understandable | Semantic HTML; page title matches H1; language declared; one topic per page |
| 3 | Useful | Content answers a specific question; content in static HTML (not JS-only) |
| 4 | Trustworthy | Author bio; citations/sources linked; publication + update dates visible; HTTPS |
| 5 | Quotable | One answer per section; short-answer paragraph before elaboration; FAQ schema |
| 6 | Fresh | dateModified in JSON-LD and meta; content reviewed when topic changes |
Operating Modes
Mode 1 — Create (new GEO-ready page)
- Plan page structure: one topic, one H1, question-based H2s/H3s.
- Apply
templates/page-metadata.html(canonical, hreflang, meta description). - Add
templates/techarticle.jsonld(orfaqpage.jsonldfor FAQ pages). - Write content in the quotable outline pattern (
templates/quotable-article-outline.md): short direct answer → supporting detail → sources. - Update
robots.txtto allow AI crawlers (templates/robots-ai-crawlers.txt). - Add or update
llms.txtif the site wants to guide AI agents (templates/llms.txt). - Run the GEO page checklist (in
references/pillars-and-workflow.md).
Mode 2 — Audit (score an existing page or site)
- Crawl check: read
robots.txt— areOAI-SearchBotandBingBotallowed? - Structured data: validate all JSON-LD against the Rich Results Test and Schema Markup Validator.
- Pillar sweep: for each of the six pillars, mark pass / partial / fail.
- Produce a prioritized findings table (Pillar → Finding → Severity → Fix).
- Identify quick wins (metadata, schema, robots) vs. content rewrites.
Mode 3 — Improve (apply fixes)
- Apply fixes in severity order: blockers first (crawl access, broken schema), then quick wins (metadata, dates), then content improvements.
- Re-validate structured data after every schema change.
- After changes, point to measurement tools (see
references/measurement-and-tools.md) so the user can track AI visibility over time.
Guardrails
- Never promise that changes will cause a specific AI engine to cite the page. Citation is an engine decision.
- Structured data must match visible page content exactly. Mismatches violate Google's policies and can suppress the page.
llms.txtis optional. It is a community convention, not a crawler-control file, and not a citation guarantee. Recommend it only when the site wants to guide AI agent navigation.robots.txtis the only authoritative crawler-control file.llms.txthas no effect on crawling.- Do not add
noindexorDisallowfor AI crawlers unless the user explicitly wants to block AI indexing. - Prefer primary platform documentation (Google Search Central, Bing Webmaster Tools, Schema.org) over third-party summaries.
Examples
Example 1 — Audit request
User: "Can you audit my blog for AI search visibility?"
Actions:
- Check
robots.txt→OAI-SearchBotis missing aDisallowbut also missing an explicitAllow— confirm default is allow. - Validate JSON-LD on the homepage →
datePublishedis missing,authorhas nourl. - Run pillar sweep → Trustworthy: partial (no author bio page); Quotable: fail (no FAQ schema on FAQ page).
- Return findings table with three priority tiers.
Result: Prioritized list: fix techarticle.jsonld, add author bio, add FAQPage schema. Clear, actionable, no ranking promises.
Show full SKILL.md (355 more words)Show less
Example 2 — Create request
User: "Create a new GEO-optimized article page for my Next.js blog."
Actions:
- Draft
<head>fromtemplates/page-metadata.html. - Generate
templates/techarticle.jsonldfilled with real title, author, dates. - Structure content using
templates/quotable-article-outline.md: direct-answer intro, H2/H3 sections, sources list. - Confirm
robots.txtallowsOAI-SearchBot. - Run checklist — all eight items pass.
Result: Ready-to-deploy page with correct metadata, valid schema, and citation-ready prose.
Example 3 — llms.txt request
User: "Write an llms.txt for my documentation site."
Actions:
- Inventory the three or four most useful pages for an AI agent.
- Apply
templates/llms.txtformat: H1 site name → blockquote description →## Key pageswith Markdown links → optional## Technical files. - Remind the user that
llms.txtis not a crawler-control file and doesn't guarantee citations.
Result: A concise, standards-compliant llms.txt with honest caveats.
Troubleshooting
| Symptom | Likely cause | Fix |
|---|---|---|
| Rich Results Test shows no schema | JSON-LD is in a JS-rendered <script> tag loaded after DOMContentLoaded | Move JSON-LD to a static <script type="application/ld+json"> in server-rendered HTML |
| Schema validation error: "required property missing" | datePublished, author, or headline absent | Add all required fields; check Schema.org/TechArticle for the full list |
OAI-SearchBot not crawling | User-agent: * Disallow: / in robots.txt blocks all bots | Add explicit Allow: / for OAI-SearchBot above the wildcard rule |
llms.txt not picked up by agents | File not at https://example.com/llms.txt (must be root) | Move file to domain root; verify it returns Content-Type: text/plain |
| Content visible in browser but not cited | Content rendered by client-side JS only | Render content server-side so crawlers receive it in the initial HTML response |
References and Templates
Load these files on demand — only when the task requires the detail.
| File | Load when |
|---|---|
references/pillars-and-workflow.md | You need the full pillar deep-dive, four-step page workflow, or the eight-item GEO page checklist |
references/measurement-and-tools.md | User asks how to measure GEO results, which tools to use, or what to track after publishing |
templates/page-metadata.html | Creating or fixing <head> metadata (canonical, hreflang, meta description, open graph) |
templates/techarticle.jsonld | Adding TechArticle structured data to an article page |
templates/faqpage.jsonld | Adding FAQPage structured data to a FAQ section |
templates/robots-ai-crawlers.txt | Updating robots.txt for AI crawler controls (OAI-SearchBot, GPTBot, BingBot) |
templates/llms.txt | Writing or updating the site's llms.txt |
templates/quotable-article-outline.md | Structuring article content for AI citation |
© tech-leads-club, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 8 other files (references) in packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization of tech-leads-club/agent-skills.
- SKILL.md
- references/measurement-and-tools.md
- references/pillars-and-workflow.md
- templates/faqpage.jsonld
- templates/llms.txt
- templates/page-metadata.html
- templates/quotable-article-outline.md
- templates/robots-ai-crawlers.txt
- templates/techarticle.jsonld
Open the folder on GitHubat commit 120b676
Compare with similar skills
Generative Engine Optimization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Generative Engine Optimization this skilltech-leads-club/agent-skills | 7k | — | ~2.5k | Automated safety check: Pass | MIT | |
| GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude | 11k | — | ~2.8k | Automated safety check: Notes | MIT | |
| SEONexus-JPF/note-companion | 870 | — | ~2.2k | Automated safety check: Pass | MIT | |
| SEOAgriciDaniel/seo-os | 134 | 2 repos | ~3.5k | Automated safety check: Pass | MIT | |
| SEOAgriciDaniel/codex-seo | 791 | — | ~3.7k | Automated safety check: Pass | MIT | |
| SEO And Aeo Strategymanojbajaj95/claude-gtm-plugin | 105 | — | ~4k | Automated safety check: Pass | MIT |
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Questions about Generative Engine Optimization
What does Generative Engine Optimization do?
Makes a page or site easier for AI answer engines to find, understand, trust and quote, using metadata, structured data, an llms.txt file and clear page structure. The skill treats GEO as documentation quality rather than a trick: correct metadata, honest structured data, clear prose and stable URLs. It tells the agent never to promise rankings or AI citations, since those are decisions the engines make.
When should I use Generative Engine Optimization?
Generative Engine Optimization fits situations like: preparing a page that AI answer engines can parse and quote; writing an llms.txt file for a site; adding FAQ or article structured data to a page for AI answers; auditing a codebase for generative search readiness.
How do I install Generative Engine Optimization in Claude Code?
Run `npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a claude-code`. Or copy the skill folder (packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization in tech-leads-club/agent-skills) into .claude/skills/tlc-generative-engine-optimization in your project. Claude Code loads it when a task matches its description.
How do I install Generative Engine Optimization in Codex?
Run `npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a codex`. Or copy the skill folder (packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization in tech-leads-club/agent-skills) into .agents/skills/tlc-generative-engine-optimization in your project. Codex loads it when a task matches its description.
Can I use Generative Engine Optimization in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tech-leads-club/agent-skills --skill tlc-generative-engine-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tlc-generative-engine-optimization, .gemini/skills/tlc-generative-engine-optimization, .github/skills/tlc-generative-engine-optimization and .opencode/skills/tlc-generative-engine-optimization in your project.
What does Generative Engine Optimization need to run?
SKILL.md names no scripts, command-line tools or credentials: Generative Engine Optimization is instructions for the agent only.
Does Generative Engine Optimization access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Generative Engine Optimization safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Generative Engine Optimization use?
Generative Engine Optimization is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Generative Engine Optimization use?
About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.8k tokens, read only when the agent opens those files.
What are the alternatives to Generative Engine Optimization?
Skills that share tags, products or a category with Generative Engine Optimization: GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars), SEO (Nexus-JPF/note-companion, 870 stars), SEO (AgriciDaniel/seo-os, 134 stars) and SEO (AgriciDaniel/codex-seo, 791 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Generative Engine Optimization?
tech-leads-club (a GitHub organization) maintains it in tech-leads-club/agent-skills, which has 7,041 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on September 20, 2026.
Source: tech-leads-club/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.