Marketing Skills is an open-source library of reusable workflows that helps AI coding agents perform marketing and SEO tasks. It serves people working on search optimization, content, advertising, launches, analytics, and related marketing activities, and its catalogue entries are the individual skills agents can install.
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 kostja94/marketing-skills --skill translationgit clone --depth 1 https://github.com/kostja94/marketing-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/kostja94/marketing-skills/translation)<a href="https://agentmods.dev/skills/kostja94/marketing-skills/translation"><img src="https://agentmods.dev/badge/skills/kostja94/marketing-skills/translation/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/kostja94/marketing-skills/translation"><img src="https://agentmods.dev/badge/skills/kostja94/marketing-skills/translation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00060 | $0.01344 |
| Opus 5.5 | $0.00024 | $0.00538 |
| Sonnet 5.5 | $0.00012 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
translation 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 20d 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- translation — 100% identical, 271 lines differ
- translation — 100% identical, 271 lines differ
- translation — 100% identical, 271 lines differ
- translation — 100% identical, 271 lines differ
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Translation
Own the language-production lifecycle. Deliver natural, accurate target-language content without changing product facts, inventing market claims, or treating translated words as proof that a locale is ready to launch.
Boundaries
- This skill owns translation, transcreation, terminology, style, linguistic review, and keeping translations current.
- localization-strategy owns locale selection, page coverage, URL architecture, routing, rollout, and release verification.
- keyword-research owns target-market queries. Never translate a source keyword list and call it localized research.
- Project positioning, feature availability, legal facts, and approved terminology remain in their project SSOTs.
Prepare the Source
Read root contextus.md when present. Before translating, establish:
- source version and owner;
- content type and target locale or market;
- user task, audience, tone, and channel;
- product facts and claims that must remain unchanged;
- approved terminology, forbidden terms, and terms intentionally left untranslated;
- layout, UI, metadata, structured-data, or character constraints;
- review level required by business, legal, safety, or conversion risk.
If the source is unstable or contradictory, report the conflict before producing many dependent translations.
Choose the Right Treatment
| Treatment | Use when | Main risk |
|---|---|---|
| Direct translation | Meaning and context transfer cleanly | Literal but unnatural phrasing |
| Localization | Formats, examples, terminology, or market facts differ | Unverified adaptation |
| Transcreation | Taglines, campaigns, landing-page persuasion, or cultural framing must change | Drifting from the product promise |
| Machine-assisted translation with review | Volume is high and risk is controlled | Fluent factual or terminology errors |
| Specialist translation | Legal, regulated, safety-critical, or technically exact material | Liability from semantic change |
Machine translation is a production method, not an automatic quality verdict. Match review depth to risk and page importance. Do not publish raw machine output merely because it reads fluently.
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.
- 20d ago Changed · -89 lines · -19 tokens per session b9ec2c518fb6
- 1mo ago Changed ddd96d432373
- 1mo ago First seen · 223 lines · 79 tokens per session scan A 78f5d4dab638
translation is a skill published in the GitHub repository kostja94/marketing-skills (1,065 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 1,344 once invoked, about $0.0002 per session on Opus 5.5. 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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