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Blog Localize

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AgriciDaniel
blog-localize

Deep cultural adaptation of translated blog posts. Run after blog-translate completes. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "lokalisieren", "localiser", "adaptar".

Overview

PublisherAgriciDaniel
Repositoryclaude-blog
Skill nameblog-localize
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 Localize 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-localize .claude/skills/blog-localize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog Localize 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 Localize 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 Localize 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 Localize, Cultural Deep-Adaptation

Takes a translated blog post and performs cultural adaptation so the result feels like it was written for the target market, not translated into it. This is the layer above blog-translate: it replaces examples, adjusts tone, swaps references, and localizes the entire reading experience.

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

Key References

  • ../blog-translate/references/cultural-adaptation.md, the shared cultural profiles file with substitution tables for DACH, Francophone, Hispanic, Japanese, and a custom template. Do not duplicate this file.

When to Use

  • Right after blog-translate produces a base translation.
  • When existing translated content reads like "translated from English".
  • When targeting a specific market, not just a language.
  • When content needs local statistics, examples, and brand references.

Workflow

Phase 1: Locale Understanding

  1. Parse the locale code with the shared multilingual locale rules used by blog-translate, blog-multilingual, and blog-locale-audit: ISO 639-1 language in lowercase, optional ISO 15924 script in title case, optional ISO 3166-1 Alpha-2 region in uppercase. Accept full codes (de-DE, fr-CA, es-MX, pt-BR, zh-Hant) and unambiguous plain language codes (de, fr). Require a region or explicit neutral mode for ambiguous language-only targets such as es, pt, and zh.
  2. Load the cultural profile from ../blog-translate/references/cultural-adaptation.md.
    • If the locale has a profile, use it.
    • If not, follow the "Custom-locale template" section in that reference to build a minimal profile inline.
  3. Read the translated post only after resolving it inside the project root/current working directory. Reject symlinked paths, traversal outside the root, files over 10 MB, and binary files. Then identify adaptation targets.

Phase 2: Cultural Audit

Scan for elements that signal foreign origin:

ElementWhat to look for
Brand examplesUS or UK brands with no relevance locally
Statistics sourcesUS-only studies and surveys
CTAsAmerican-style aggressive calls-to-action
IdiomsLiterally translated English expressions
Legal referencesForeign laws (CCPA, FTC) where local law applies (DSGVO, RGPD)
Cultural referencesForeign holidays, events, customs
Currency and pricingUSD without conversion or context
ToneToo casual or too formal for the target market
Address formInconsistent Sie/du, tu/vous, formal/informal

Output an audit report listing every target with severity (critical, recommended, optional).

Phase 3: Adaptation

3a. Example Substitution

Swap foreign examples for local equivalents:

  • Use WebSearch to find local case studies, brands, or scenarios.
  • Replace inline, preserving the same argument and structure.
  • Record source URL, access date, and rationale for every non-obvious local replacement.
  • If no local equivalent exists, keep the original but add local context ("In the German market, the equivalent dynamic is X").
3b. Statistics Localization
  • Use primary or high-quality local sources for replacement statistics: national statistics offices, regulators, official industry bodies, academic datasets, or named research reports with methodology.
  • Do not rely on generic WebSearch snippets as evidence. Fetch the cited page, verify the figure and context, and record the source URL and date.
  • Fetch cited pages only after SSRF checks: allow https URLs only; reject javascript:, data:, file:, localhost, loopback, private, link-local, multicast, and reserved IPs after DNS resolution; disable redirects or validate the final URL with the same checks; cap redirects, response size, and request time; log the final URL and access date.
  • If local data exists with comparable methodology, swap the source and the figure together. Keep one named source per claim.
  • If local data is related but uses a different methodology or timeframe, do not silently swap it. Keep the original claim scoped, or rewrite the claim to match the local source.
  • If not, keep the original stat but mark its geographic scope ("In the US, ...").
  • Never strip source attribution.
3c. CTA Adaptation

Rewrite calls-to-action per the cultural profile:

  • Adjust aggressiveness level (DACH and JA prefer informational, US prefers imperative).
  • Use culturally appropriate action verbs.
  • Adapt urgency framing.
3d. Tone Calibration
  • Match formality per profile (DACH defaults to Sie for B2B, du for B2C lifestyle; FR defaults to vous; JA shifts register sharply by audience).
  • Ensure consistent formal or informal address throughout the entire document.
  • Match local content-style conventions.
3e. Legal and Regulatory Context
  • Map legal references by issue and jurisdiction. Keep the original law when the claim is specifically about US compliance. Only substitute when the local law addresses the same issue, such as CCPA to DSGVO in DE, RGPD in FR, LGPD in BR, LFPDPPP in MX, Ley 1581 in CO, or Ley 25.326 in AR.
  • Add local compliance notes where they help the reader.
  • Remove irrelevant foreign regulatory references.
3f. Brand Example Swaps (Quick Map)

Profiles in ../blog-translate/references/cultural-adaptation.md provide substitution tables. Common examples:

Source (US)DACHFRES (Spain)LATAMJA
WalmartMediaMarktCarrefourEl Corte InglésWalmart MXAeon
TargetSaturnAuchanHipercorLiverpoolIto-Yokado
FTCBundeskartellamtDGCCRFCNMCPROFECO (MX)JFTC
CCPADSGVORGPDRGPDLFPDPPP (MX), Ley 1581 (CO), Ley 25.326 (AR), LGPD (BR)APPI

Phase 4: Quality Verification

  • All critical adaptation targets addressed.
  • Tone is consistent throughout.
  • No remaining foreign-origin markers.
  • Statistics have valid sources (original or localized).
  • CTAs match cultural expectations.
  • Formal or informal address is consistent end to end.
  • Content still supports the same argument as the original.
  • SEO elements remain optimized beyond keyword placement: localized title and meta, heading intent, slug, alt text, internal-link anchors, same-language canonical, hreflang compatibility, and schema inLanguage.
  • Word count is within the expected ratio for the language pair.

Phase 5: Save and Report

  1. Save the localized version. Default: write a reviewed copy as {slug}-localized.{ext}. Only overwrite the translated file when the user asks for overwrite; before overwriting, create a timestamped backup and show a diff summary. Resolve every output path inside the project root and reject traversal, symlinked paths, or writes outside that root.

  2. Present the summary:

    ## Localization complete: [Title]
    
    ### Target locale: [locale-code] ([locale-name])
    
    ### Adaptations made
    | Type | Count | Examples |
    |------|-------|----------|
    | Brand examples | [N] | Walmart -> MediaMarkt |
    | Statistics | [N] | US survey -> DACH survey |
    | CTAs | [N] | "Buy now" -> "Jetzt entdecken" |
    | Tone adjustments | [N] | Casual -> Sie |
    | Legal references | [N] | CCPA -> DSGVO |
    | Cultural references | [N] | Thanksgiving -> Weihnachtsgeschaeft |
    
    ### Cultural fit score
    - Naturalness: [1-10]
    - Market relevance: [1-10]
    - Tone match: [1-10]
    - Overall: [N]/30
    
    ### Remaining recommendations
    - [Optional adaptations not applied]

Error Handling

ScenarioAction
No cultural profile for the localeBuild a minimal profile from the custom-locale template, proceed
File is not in the expected languageWarn the user, offer to translate first
No local statistics availableKeep the original stat with a geographic-scope note
Locale code ambiguous (e.g., pt)Ask: "Did you mean pt-BR (Brazil) or pt-PT (Portugal)?"

Cross-References

  • Pre-step (translation): /blog translate <file> --to <code>
  • QA across language versions: /blog locale-audit <directory>
  • One-command pipeline: /blog multilingual <topic> --languages <codes>

Frequently asked questions

What does the Blog Localize AI skill do?

Deep cultural adaptation of translated blog posts. Run after blog-translate completes. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "lokalisieren", "localiser", "adaptar".

Why use Blog Localize on TypingMind?

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

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

Which AI models can use Blog Localize?

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 Localize?

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

Is the Blog Localize 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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