translation

translation is a skill for Claude Code, Codex from seb1n/awesome-ai-agent-skills. It costs 44 tokens per session (1,563 once invoked), scanned A, original, MIT.

A language-translation workflow that adapts meaning, tone, cultural references, and specialist terms for the target language. It can handle technical documents, marketing copy, interface text, legal text, and general writing.

In plain words
What is it for?
Use it to translate documentation, advertisements, user-interface strings, legal material, and other text while preserving the original structure and intended audience.
Why use it?
It avoids awkward word-for-word translations and keeps terminology and formatting consistent across a document.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to translate documentation, advertisements, user-interface strings, legal material, and other text while preserving the original structure and intended audience.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/seb1n/awesome-ai-agent-skills/translation
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.

Any agent
npx skills add seb1n/awesome-ai-agent-skills --skill translation
Clone the repo
git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for translation

README.md
[![agentmods](https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/translation/github.svg)](https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/translation)
Your own site
<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/translation"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-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.

agentmods 80×15 button for translation

Your own site · 80×15
<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/translation"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/translation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,563 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 52
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.01563
Opus 5 $0.00022 $0.00781
Sonnet 5 $0.00009 $0.00313
Haiku 4.5 $0.00004 $0.00156

Measured 9d ago against content hash eab67964eadb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

writing-and-content/translation/SKILL.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Translation

This skill enables an AI agent to translate text between languages while preserving meaning, tone, and context. It goes beyond word-for-word substitution by handling idiomatic expressions, cultural nuance, domain-specific terminology, and formality registers. The agent can translate technical documentation, marketing copy, UI strings, legal text, and general prose, adapting output to the conventions of the target locale.

Workflow

  1. Analyze Source Context Examine the source text to determine its domain (technical, marketing, legal, casual), register (formal, informal, neutral), and intended audience. Identify any idiomatic expressions, culturally specific references, or humor that will require adaptation rather than literal translation. Note the document format (plain text, Markdown, JSON, HTML) so structure is preserved in the output.

  2. Research Terminology For specialized content, build or consult a terminology glossary to ensure consistency. Technical documents require exact translations of domain terms (e.g., "endpoint" stays "endpoint" in many languages or maps to an accepted equivalent). Marketing copy may need creative transcreation rather than direct translation. If the user provides a glossary or translation memory, integrate it before proceeding.

  3. Translate the Content Produce the translation following the determined tone, formality level, and terminology. Preserve all formatting markers such as Markdown headings, code blocks, HTML tags, and JSON keys. For UI strings, keep placeholder tokens (e.g., {username}, %d) intact and in the correct grammatical position for the target language. Handle pluralization rules specific to the target language.

  4. Localize Cultural References Adapt units of measurement, date formats, currency symbols, and culturally bound metaphors to the target locale. For example, convert miles to kilometers when translating for a European audience, or replace an American sports analogy with one that resonates in the target culture. For marketing content, ensure slogans and calls-to-action carry the same persuasive impact in the target language.

Read the full file on GitHub · 104 lines

Changes

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.

  1. 9d ago First seen · 104 lines · 44 tokens per session scan A eab67964eadb

Subscribe to this mod's changes

translation is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,563 once invoked, about $0.0002 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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