blog-translate
Translate existing blog posts into one or more target languages with SEO-optimized localization.
Skill by Infrasity-Labs
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/infrasity-labs-blog-translate
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, data, writing, marketing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/blog-translate
What's inside
- Skill name
blog-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 blog-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".
- License
- MIT
- Compatibility
- Standalone within claude-blog. Invoked by blog-multilingual.
- Instructions
- 174 lines in SKILL.md · view on GitHub
Files (3)
- SKILL.md
- cultural-adaptation.md · references/
- translation-rules.md · references/
SKILL.md (first lines)
# 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.
## Key References
Load on demand:
- `references/translation-rules.md`, format preservation, number/date/currency
formats per locale, quote handling, quality criteria.
- `references/cultural-adaptation.md`, cultural profiles per locale (DACH,
Francophone, Hispanic, Japanese, custom). This file is shared with
`blog-localize` (do not duplicate).
## 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.
- Pointers to `references/translation-rules.md` and the cultural profile in
`references/cultural-adaptation.md` if one exists for the target locale.
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:
```yaml
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%, others see `references/translation-rules.md`).
- FAQ count matches.
- Citation capsules present in each H2.
3. Save translated files:
```
translations/
{lang}/{localized-slug}.{ext}
```
When invoked from `blog-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).From Infrasity-Labs/dev-gtm-claude-skills, MIT.
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Signals
- Stars
- 144
- Forks
- 16
- Open issues
- 1
- Last commit (this folder)
- Jun 9, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
blog-translate skill. Agent Mart. https://agentmart.dev/skills/infrasity-labs-blog-translate (last updated 2026-10-24)