Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill blog-translategit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-translate)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-translate"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-translate/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-translate"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-translate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00136 | $0.01657 |
| Opus 5 | $0.00068 | $0.00829 |
| Sonnet 5 | $0.00027 | $0.00331 |
| Haiku 4.5 | $0.00014 | $0.00166 |
Grade A, and why
blog-translate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 withblog-localize(do not duplicate).
Workflow
Phase 1: Input Parsing
- Read the source file (markdown, MDX, or HTML).
- Auto-detect source language. Order of preference:
- Frontmatter
langfield. - HTML
langattribute. - Content analysis (script, common stop words).
- Frontmatter
- Parse target languages from
--toas comma-separated ISO 639-1 codes (de,fr,es,ja,pt-BR). If--tois missing, ask the user once: "Which languages should I translate to? Provide ISO 639-1 codes (e.g., de, fr, es, ja, pt-BR)." - Validate every code. Reject invalid ones with a suggestion (
jpbecomes "Did you meanjafor 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
alttext 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).
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 192 lines · 136 tokens per session scan A aceaa4a58c75
blog-translate is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 136 tokens to every session and 1,657 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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