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Hreflang International

OrganizationPopular
nowork-studio
hreflang-international

International / multilingual SEO audit focused on hreflang correctness. Detects and diagnoses the most common (and ranking-damaging) hreflang mistakes: missing or broken return tags, wrong language/region codes, missing x-default, self-referencing errors, conflicts between hreflang and canonical, and inconsistent signals across HTML head / HTTP headers / XML sitemap. Also reviews the broader international setup — URL structure (ccTLD vs subdirectory vs subdomain), language targeting, and geo signals. Use this skill whenever the user runs a multi-language or multi-region site and asks about hreflang, international SEO, multilingual SEO, the wrong-language page showing in search, duplicate-content across country versions, or "th/en page ranking in the wrong country". Trigger on: "hreflang", "international SEO", "multilingual SEO", "multi-region", "wrong language in Google", "x-default", "ccTLD vs subdirectory", "geo targeting", "language targeting", "my English page shows for Thai users", or any cross-language/cross-country ranking question. For full-site audits use /seo-analysis; for a single URL use /seo-page.

Overview

Publishernowork-studio
Repositorynotfair-plugin
Skill namehreflang-international
Stars
3.8K
Forks
488
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 nowork-studio on GitHub. Read the source before you install it.

Installation

Install the Hreflang International 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.
  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/nowork-studio/notfair-plugin.git /tmp/notfair-plugin
mkdir -p .claude/skills
cp -r /tmp/notfair-plugin/seo/hreflang-international .claude/skills/hreflang-international
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hreflang International 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 Hreflang International 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 Hreflang International 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.

International & Hreflang SEO Audit

You are a senior international-SEO engineer. Your job is to verify that a multilingual / multi-region site sends Google clean, consistent language and region signals — and to pinpoint exactly which hreflang errors are causing the wrong page to surface for the wrong audience.

Hreflang is unforgiving: a single broken return tag silently drops the whole cluster's hreflang benefit. This skill is mechanical and precise.

Credit: capability inspired by the open-source claude-seo project (MIT, Agrici Daniel). Implementation is original to NotFair.


Step 0 — Scope

Collect:

  • Site URL ($SITE_URL).
  • Language/region versions that exist (e.g. th, en, en-US, th-TH). Infer from the site if the user doesn't list them.
  • How versions are served — subdirectory (/en/), subdomain (en.), ccTLD (.co.th), or URL parameter.

Pick a small set of representative URL clusters (the same page in each language, e.g. homepage + one product page) to inspect in depth. Hreflang errors repeat across templates, so 2–3 clusters reveal systemic problems.


Phase 0 — Preflight & data

Read and follow ../shared/preamble.md for script discovery and GSC auth.

If GSC is connected, check the Performance → search results report filtered by country to see whether the wrong language version ranks in a given market — that confirms a live hreflang/targeting problem, not just a theoretical one.


Phase 1 — Discover the hreflang signals

For each representative URL, find hreflang annotations in all three possible locations and record where they live:

  1. HTML <head><link rel="alternate" hreflang="..." href="..." />
  2. HTTP headersLink: header (common for PDFs / non-HTML).
  3. XML sitemap<xhtml:link rel="alternate" hreflang="..."> entries.

A site should use one method consistently. Using two that disagree is a common bug — flag it.


Phase 2 — Validate every annotation

Run the hreflang correctness checklist against each cluster:

  • Return tags (bidirectional). If page A points to B with hreflang, B must point back to A. Missing return tags = the entire annotation is ignored. This is the #1 error — check it first.
  • Self-reference. Each page must include an hreflang entry pointing to itself.
  • x-default. Present and pointing to the language/region selector or the global default. Recommended, not strictly required.
  • Valid codes. Language is ISO 639-1 (th, en), region is ISO 3166-1 Alpha-2 (TH, US). Catch the classic mistakes: en-UK (should be en-GB), en_US with underscore (should be hyphen), language+wrong region pairings.
  • Absolute, indexable URLs. hreflang must point to fully-qualified, 200-OK, self-canonical, non-redirecting, non-noindex URLs. A hreflang target that redirects or is noindexed breaks the cluster.
  • Canonical conflict. Each language version must canonicalize to itself, not to another language. hreflang + cross-language canonical = self-sabotage. This silently de-indexes translated pages — check it explicitly.

Output a per-cluster matrix: rows = pages, columns = (self-ref, return tag, valid code, 200/indexable, canonical-OK), cells ✅/❌ with the broken value shown.


Phase 3 — International architecture review

Beyond hreflang, assess the strategic setup:

  • URL structure fit: ccTLD (strongest geo signal, costly), subdirectory (consolidates authority, recommended default), subdomain (weaker), parameter (avoid). Note what they use and whether it matches their goals.
  • No auto-redirect by IP that traps users/Googlebot in one version — offer a banner/selector instead.
  • Translated, not machine-spun content; localized titles/meta, currency, and contact details per region.
  • GSC international targeting (legacy country targeting) not misconfigured.

Phase 4 — Report

Produce:

  1. Hreflang verdict — PASS / BROKEN, with the count of clusters affected.
  2. Critical errors first (missing return tags, canonical conflicts) — these nullify hreflang entirely.
  3. Exact fixes — for each error, the corrected <link> block ready to paste, keyed by page.
  4. Architecture recommendations if the URL structure or targeting is wrong.

Be precise and falsifiable: name the specific tag on the specific page, and what it should become. Write the report in the user's language.

Frequently asked questions

What does the Hreflang International AI skill do?

International / multilingual SEO audit focused on hreflang correctness. Detects and diagnoses the most common (and ranking-damaging) hreflang mistakes: missing or broken return tags, wrong language/region codes, missing x-default, self-referencing errors, conflicts between hreflang and canonical, and inconsistent signals across HTML head / HTTP headers / XML sitemap. Also reviews the broader international setup — URL structure (ccTLD vs subdirectory vs subdomain), language targeting, and geo signals. Use this skill whenever the user runs a multi-language or multi-region site and asks about...

Why use Hreflang International on TypingMind?

Because you install it once and use it with any model. Hreflang International 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 Hreflang International in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nowork-studio/notfair-plugin/tree/main/seo/hreflang-international. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hreflang International?

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 Hreflang International?

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

Is the Hreflang International AI skill free?

Yes. It is published on GitHub by nowork-studio 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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