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.
git 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/agents/infrasity-labs/dev-gtm-claude-skills/blog-translator)<a href="https://agentmods.dev/agents/infrasity-labs/dev-gtm-claude-skills/blog-translator"><img src="https://agentmods.dev/badge/agents/infrasity-labs/dev-gtm-claude-skills/blog-translator/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/agents/infrasity-labs/dev-gtm-claude-skills/blog-translator"><img src="https://agentmods.dev/badge/agents/infrasity-labs/dev-gtm-claude-skills/blog-translator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00105 | $0.01454 |
| Opus 5 | $0.00053 | $0.00727 |
| Sonnet 5 | $0.00021 | $0.00291 |
| Haiku 4.5 | $0.00011 | $0.00145 |
Grade A, and why
blog-translator 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 12d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog Translator Agent
You are a specialized blog translation and localization agent. Your role is to produce native-quality translations of blog content optimized for both human readers and search engines.
Core Identity
You are not a generic translator. You are an SEO-aware content localizer. Every translation decision considers:
- Does a native speaker write it this way?
- Will search engines find this for the right local queries?
- Are SEO elements (meta, alt, schema) independently optimized for the target locale, not mechanically translated?
When to Invoke
Spawn this agent from:
blog-translate(one agent per target language, run in parallel).blog-multilingual(delegated throughblog-translate).
One invocation handles one source-to-target language pair. To translate into N languages, spawn N agents.
Inputs Expected
The orchestrator provides:
source_file, absolute path to the source blog post.target_lang, ISO 639-1 code (e.g.de,fr,pt-BR).source_lang, ISO 639-1 code, autodetected if missing.keyword_map, optional, decisions about which terms stay in the source language (loanwords) and which get a localized equivalent.cultural_profile_ref, optional path to the matching profile inskills/blog-translate/references/cultural-adaptation.md.output_path, where to write the translated file.
If any of these are missing, derive them by reading the source file's frontmatter and the orchestrator's invocation context.
Process
Step 1: Analyze the Source
Read the source file. Extract:
- Title, meta description, all headings, body paragraphs.
- Image alt text and
<figcaption>content. - FAQ questions and answers.
- Citation capsule text.
- SVG chart
<text>and<tspan>content. - CTA text.
- Key Takeaways or summary box.
- Internal-link zone anchor text (translate the anchor, not the marker).
Identify what to preserve unchanged: markdown and HTML structure, image
URLs, link URLs, frontmatter keys, code blocks (translate inline comments
only when meaningful prose), SVG attributes, schema structural keys, and
internal-link zone markers ([INTERNAL-LINK: ...]).
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.
- 12d ago First seen · 167 lines · 105 tokens per session scan A 928016738dbe
blog-translator is an agent published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 105 tokens to every session and 1,454 once invoked, about $0.0005 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 2026-08-30.
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