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Site Mapping

Community
AtlasOmnia
site-mapping

site-mapping — Map out a website's full structure — sitemaps, navigation, URL taxonomy, content inventory.

Overview

PublisherAtlasOmnia
Repositorydonna-starter
Skill namesite-mapping
Stars
131
Forks
9
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AtlasOmnia on GitHub. Read the source before you install it.

Installation

Install the Site Mapping AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AtlasOmnia/donna-starter/tree/main/skills/research/site-mapping
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AtlasOmnia/donna-starter.git /tmp/donna-starter
mkdir -p .claude/skills
cp -r /tmp/donna-starter/skills/research/site-mapping .claude/skills/site-mapping
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Site Mapping in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Site Mapping on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Site Mapping is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Site Mapping

Map the complete structure of a website: extract all URLs from sitemaps, analyze navigation hierarchy, classify content by section, and produce a structured overview.

When to Use

  • User asks to "map out," "audit," or "review" a website's structure
  • Need to understand a site's URL taxonomy, content sections, or SEO footprint
  • Preparing competitive analysis, content gap assessment, or migration planning

Workflow

1. Discover sitemaps

Check these in order:

  • https://site.com/sitemap.xml (may redirect to sitemap_index.xml)
  • https://site.com/robots.txt — look for Sitemap: directive
  • Common patterns: /page-sitemap.xml, /post-sitemap.xml, numbered variants (sitemap2.xml)

2. Extract URLs programmatically

Use browser_console with JS to fetch and parse XML sitemaps — DO NOT rely on reading rendered HTML tables (they truncate):

js
(async()=>{
 const urls=[];
 for(const sm of ['page-sitemap.xml','post-sitemap.xml']){
 const r=await fetch('https://site.com/'+sm);
 const t=await r.text();
 const parser=new DOMParser();
 const doc=parser.parseFromString(t,'text/xml');
 doc.querySelectorAll('loc').forEach(l=>urls.push(l.textContent));
 }
 return urls;
})()

3. Classify by path segments

Group URLs by first/second path segment to identify sections:

js
const paths={};
urls.forEach(u=>{
 const path=u.replace('https://site.com/','');
 const parts=path.split('/').filter(Boolean);
 // Group by [product][section] pattern
});

4. Extract navigation structure

From the homepage, pull:

  • Primary nav menu items (expand dropdowns)
  • Footer links
  • Use document.querySelectorAll('nav .sub-menu li a') and footer a

5. Produce structured output

Deliver as a table or hierarchy showing:

  • Section name | URL prefix | Page count | Notes

Pitfalls

  • Don't guess the URL — if the user says "I have a site" without naming it, ask for the URL first. Do not assume based on context (e.g., assuming acme.com because the user works at Acme Corp).
  • Reddit is not sitemap-mappable in the normal sense — old.reddit.com/robots.txt currently disallows /, and Reddit's useful structure is operational surfaces (old.reddit HTML, .json endpoints, new Reddit SPA verification), not public XML sitemaps. For Reddit, load a Reddit-specific browsing skill (e.g. reddit-browse-and-post) and use it instead of crawling sitemaps.
  • Sitemap HTML tables truncate — Yoast-generated sitemaps render as HTML tables but cut off after ~100 rows. Always fetch raw XML via fetch() + DOMParser in browser_console.
  • Image/media URLs pollute counts — filter out /wp-content/uploads/ and similar asset paths when counting "pages."
  • Multiple sitemap files — Yoast commonly splits into numbered variants (page-sitemap.xml, page-sitemap2.xml). Check the index file to find all sub-sitemaps.
  • web_extract on XML returns summarized markdown, not raw data — for sitemaps specifically, use browser_console fetch instead.

Output Format

User expects a concise structured overview — table or hierarchy with section names, URL prefixes, page counts, and brief notes. No narrative preamble beyond the total scale.

Frequently asked questions

What does the Site Mapping AI skill do?

site-mapping — Map out a website's full structure — sitemaps, navigation, URL taxonomy, content inventory.

Why use Site Mapping on TypingMind?

Because you install it once and use it with any model. Site Mapping is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Site Mapping in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AtlasOmnia/donna-starter/tree/main/skills/research/site-mapping. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Site Mapping?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Site Mapping?

As many as you like. As long as a model supports skills, you can use Site Mapping with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Site Mapping AI skill free?

Yes. It is published on GitHub by AtlasOmnia under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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