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Blog Locale Audit

CommunityPopular
AgriciDaniel
blog-locale-audit

Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".

Overview

PublisherAgriciDaniel
Repositoryclaude-blog
Skill nameblog-locale-audit
Stars
2.2K
Forks
362
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 AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Blog Locale Audit 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/AgriciDaniel/claude-blog.git /tmp/claude-blog
mkdir -p .claude/skills
cp -r /tmp/claude-blog/skills/blog-locale-audit .claude/skills/blog-locale-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog Locale Audit 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 Blog Locale Audit 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 Blog Locale Audit 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.

Blog Locale Audit, Multilingual Quality Control

Audits a directory of multilingual blog content to ensure every language version is complete, consistent, correctly tagged, and SEO-optimized. Catches international content issues before they hurt rankings.

Adapted from claude-blog-multilingual by Chris Mueller (Pro Hub Challenge, March 2026). Original: https://github.com/Chriss54/multilingual-int

Workflow

Phase 1: Discovery

  1. Resolve the target directory inside the project root/current working directory. Reject symlinked directories and traversal outside the root, then scan blog content and group posts by language using:
    • Subdirectory names (en/, de/, fr/).
    • Frontmatter lang and translatedFrom fields.
    • hreflang-map.json if present.
  2. Normalize detected language codes with the shared multilingual locale rules used by blog-translate, blog-localize, and blog-multilingual: ISO 639-1 language in lowercase, optional ISO 15924 script in title case, optional ISO 3166-1 Alpha-2 region in uppercase. Flag ambiguous language-only codes such as es, pt, and zh unless the content declares an explicit neutral mode.
  3. Build a content matrix mapping which post exists in which languages. Use a stable translation-group key before comparing slugs: translationGroupId, sourceSlug, schema translationOfWork.url, or the IDs and URLs in hreflang-map.json. Fall back to normalized source slug only when no stable key exists.
  4. Detect the source language (most common translatedFrom target, or the sourceLanguage field in hreflang-map.json if present).

Phase 2: Completeness Audit

Show which translations are missing:

### Translation coverage matrix

| Post (EN) | DE | FR | ES | JA |
|-----------|----|----|----|----|
| how-to-avoid-ai-slop | ok | ok | missing | missing |
| content-marketing-2026 | ok | missing | ok | missing |

Coverage: 60% (6 of 10 expected translations present)
Missing: 4 translations needed

Phase 3: Content Parity Audit

For every post that exists in multiple languages:

CheckWhatSeverity
Section countSame number of H2 and H3 sectionsCritical
FAQ countSame number of FAQ itemsHigh
Image countSame number of imagesHigh
Chart countSame number of charts (SVG figures)High
Word count ratioWithin expected band for language pair (DE +20% to +30%, JA -20%, ES +10%)Medium
Link countSimilar internal and external link countsMedium
Evidence-backed claimsSame supported claims and citations across versionsMedium
Frontmatter parityAll required fields present per versionHigh

Flag every significant deviation as an issue.

Phase 4: SEO Parity Audit

For every language version verify:

ElementCheckSeverity
Title tagPresent, localized, clear, and appropriate for the pageCritical
Meta descriptionPresent, localized, accurate, and consistent with visible contentCritical
lang attribute or frontmatter langPresent, valid Google-compatible hreflang or BCP 47 language tagCritical
Canonical URLPoints to the same-language page, not the source-language page or x-defaultCritical
Schema inLanguageMatches langHigh
Schema translationOfWorkPoints to the source URLHigh
Alt textTranslated (no English alt in non-EN posts)High
SlugLocalized (no English slug in non-EN posts)Medium
TagsLocalizedMedium
KeywordsLocalizedMedium

Phase 5: Hreflang Audit

If hreflang-tags.html, hreflang-sitemap.xml, or hreflang-map.json exists in the directory:

CheckWhatSeverity
Self-referencingEach page references itselfCritical
Return tagsEvery relationship is bidirectionalCritical
Canonical consistencyEvery hreflang page canonicalizes to its same-language URLCritical
x-defaultPresent, points to the unmatched-language fallback such as a language selector or default market pageCritical
Language codesValid Google-compatible hreflang tags: ISO 639-1 language plus optional ISO 15924 script or ISO 3166-1 Alpha-2 regionHigh
URL consistencySame protocol, same trailing-slash conventionMedium
CompletenessEvery language version representedHigh

If no hreflang files exist, report it as a critical gap and offer: "Run /blog multilingual <topic> --languages ... to regenerate, or create hreflang-tags.html manually."

If seo-hreflang from claude-seo is installed, suggest running it for deeper validation.

Phase 6: Freshness Audit

For posts with translatedDate in frontmatter:

CheckWhatSeverity
Source updated after translationSource modified after translatedDateCritical
Source content driftStored source hash or source dateModified differs from current sourceCritical
Translation driftStored translation hash differs from current localized fileMedium
Translation older than 90 daysMay need refreshMedium
lastUpdated mismatch across versionsVersions out of syncMedium
Git or file mtime newer than translatedDateContent changed without frontmatter updateWarning

When available, store and compare sourceHash, source dateModified, translationHash, and Git mtime before relying only on translatedDate.

Emit actionable commands per stale file:

3 translations are stale:
- de/ki-trends-2026.md (source updated 2 days ago)
  -> Run: /blog translate en/ai-trends-2026.md --to de
- fr/ki-trends-2026.md (source updated 2 days ago)
  -> Run: /blog translate en/ai-trends-2026.md --to fr
- es/tendencias-ia-2026.md (translation > 90 days old)
  -> Run: /blog translate en/ai-trends-2026.md --to es

Phase 7: Report

Output as markdown by default. If the user passes --html, also write the report to locale-audit-report.html only inside the audited project root. Escape all dynamic filenames, titles, URLs, and issue text with html.escape(value, quote=True) before rendering HTML, and reject symlinked or outside-root report paths.

## Multilingual content audit report

### Summary
- Posts audited: [N] across [N] languages
- Overall health: [score] / 100
- Critical issues: [N]
- Warnings: [N]

### Translation coverage
[Matrix from Phase 2]

### Issues found
#### Critical
- [Issue with file references]

#### Warnings
- [Issue with file references]

#### Passed
- [Checks that passed]

### Prioritized fixes
1. [Highest-impact action]
2. [...]

### Stale-translation alerts
[Runnable commands from Phase 6]

### Quick fixes
- Run `/blog translate <file> --to <missing-langs>` for [N] missing translations.
- Run `/blog multilingual` to regenerate hreflang assets.
- Run `/blog localize <file> --locale <code>` for weak cultural adaptations.

Error Handling

ScenarioAction
Empty directory"No blog posts found in [path]"
Only one language presentReport coverage, suggest target languages
No hreflang filesFlag as critical gap, offer regeneration
Unrecognized file formatSkip with a warning

Cross-References

  • Fill missing translations: /blog translate <file> --to <missing-codes>
  • Deepen weak adaptations: /blog localize <file> --locale <code>
  • Regenerate hreflang assets: /blog multilingual <topic> --languages <codes>

Frequently asked questions

What does the Blog Locale Audit AI skill do?

Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".

Why use Blog Locale Audit on TypingMind?

Because you install it once and use it with any model. Blog Locale Audit 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 Blog Locale Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-blog/tree/main/skills/blog-locale-audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Blog Locale Audit?

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 Blog Locale Audit?

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

Is the Blog Locale Audit AI skill free?

Yes. It is published on GitHub by AgriciDaniel 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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