translate

name	translate
description	Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and citation capsules. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".
user-invokable	true
argument-hint	<file> --to <comma-separated-codes>
license	MIT

Blog Translate, SEO-Optimized Blog Translation

Translates an existing blog post into one or more target languages. Unlike generic translation, this skill produces SEO-optimized, publication-ready content with localized keywords, meta tags, and culturally correct formatting.

Workflow

Phase 1: Input Parsing

1. Read the source file (markdown, MDX, or HTML).
2. Auto-detect source language. Order of preference:
   • Frontmatter lang field.
   • HTML lang attribute.
   • Content analysis (script, common stop words).
3. Parse target languages from --to as comma-separated ISO 639-1 codes (de,fr,es,ja,pt-BR). If --to is missing, ask the user once: "Which languages should I translate to? Provide ISO 639-1 codes (e.g., de, fr, es, ja, pt-BR)."
4. Validate every code. Reject invalid ones with a suggestion (jp becomes "Did you mean ja for Japanese?"). If a target equals the source language, skip it with a notice.

Phase 2: Content Analysis

Extract the translatable surface:

• Frontmatter: title, description, tags, author (only when translatable, e.g. role labels, not personal names).
• All headings (H1, H2, H3).
• Body paragraphs.
• Image alt text and <figcaption> content.
• Chart <text> and <tspan> content; preserve every SVG attribute (x, y, font-size, fill, transform).
• FAQ questions and answers.
• Citation capsule text.
• Key Takeaways or summary box.
• CTA text.
• Internal-link zone anchor text.

Preserve unchanged:

• Markdown and HTML structure, tags, attributes.
• Image URLs, link URLs, frontmatter keys.
• Code blocks (translate inline comments only when meaningful).
• Internal-link zone markers ([INTERNAL-LINK: ...]).
• Source organization names in citations (Gartner, McKinsey, etc.).
• Person names.
• Schema JSON-LD blocks (translate only the user-facing string values).

Identify the primary and secondary keywords for Phase 3.

Phase 3: Keyword Localization

For each target language:

1. Decide whether the source keyword is the established term in the target market. If yes (e.g., "Content Marketing" stays in German), keep it.
2. If a local equivalent has real search behavior, swap to it.
3. Apply the same logic to secondary keywords.
4. Record the mapping. The translator agent uses it to update title, meta description, and H2 headings consistently.

Phase 4: Translation

Spawn the blog-translator agent (via Task) for each target language with:

• The source content.
• The keyword localization map from Phase 3.
• The target language code.

Run agents in parallel when translating into multiple languages.

The agent returns the fully translated post in the same format as the input.

Phase 5: Post-Processing

For each translated version:

1. Add or update locale frontmatter:

   lang: "de"
   translatedFrom: "en"
   translatedDate: "YYYY-MM-DD"
   slug: "wie-man-ki-slop-vermeidet"
   

2. Verify structural integrity:
   • Same number of H2 and H3 sections as the original.
   • All images present with translated alt text.
   • All SVG charts present with translated text labels (length-adjusted: DE +30%, FR +15%, JA -20%).
   • FAQ count matches.
   • Citation capsules present in each H2.
3. Save translated files:

   translations/
     {lang}/{localized-slug}.{ext}
   

   When invoked from multilingual, save into multilingual/{lang}/{localized-slug}.{ext} instead.

Phase 6: Translation-Quality Guardrails

Scan the output for machine-translation artifacts before reporting done:

• Literal idioms (English idioms transliterated, not adapted).
• Unnatural word order.
• Mixed-language sentences (other than established loanwords).
• Number, date, or currency strings still in source format.
• Frontmatter strings still in the source language.

Flag every issue inline (file path, line number, fix suggestion). The translator agent should re-pass any flagged passage before delivery.

Phase 7: Delivery

## Translation complete: [Original title]

### Source
- Language: [source]
- File: [source path]

### Translations
| Language | File | Keywords adapted | Status |
|----------|------|------------------|--------|
| de | translations/de/{slug}.md | [N] | ok |
| fr | translations/fr/{slug}.md | [N] | ok |

### Quality checks
- Structural integrity: pass / fail per language
- Meta tags localized: pass / fail per language
- Numbers, dates, currencies formatted per locale: pass / fail
- Keywords localized: [N] keywords adapted
- Machine-translation artifacts flagged: [N] (see notes above)

### Next steps
- Run `/smart-blog-skills:localize <file> --locale <code>` for cultural deep-adaptation.
- Run `/smart-blog-skills:locale-audit translations/` to verify completeness.
- Use `/smart-blog-skills:multilingual` to combine write, translate, localize, hreflang
  in one command.

Error Handling

Scenario	Action
Unsupported language code	Suggest the correct ISO 639-1 code
Source equals a target	Skip with "Source is already in [lang]"
File not found	Report error with suggested path
Translator agent timeout	Retry once, then report partial results
Binary or non-text file	Report error, suggest correct file

Cross-References

• Next step (cultural depth): /smart-blog-skills:localize <file> --locale <code>
• QA sweep across all language versions: /smart-blog-skills:locale-audit <directory>
• One-command pipeline: /smart-blog-skills:multilingual <topic> --languages <codes>