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 agentmods add skills/furkangonel/cowrangler/localizationnpx skills add furkangonel/cowrangler --skill localizationgit clone --depth 1 https://github.com/furkangonel/cowranglerWrote 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/furkangonel/cowrangler/localization)<a href="https://agentmods.dev/skills/furkangonel/cowrangler/localization"><img src="https://agentmods.dev/badge/skills/furkangonel/cowrangler/localization.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.00740 |
| Opus 5 | $0.00013 | $0.00370 |
| Sonnet 5 | $0.00005 | $0.00148 |
| Haiku 4.5 | $0.00003 | $0.00074 |
Grade A, and why
localization 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 5d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Localization Skill
Goal
Produce target-language content that feels like it was written natively — not translated. Preserve meaning and intent while adapting cultural references, idioms, tone, and register for the target audience.
Distinction: Translation vs. Localization vs. Transcreation
| Mode | When to use |
|---|---|
| Translation | Technical docs, legal text, factual content — accuracy > naturalness |
| Localization | UI strings, user-facing messages, product copy — natural + accurate |
| Transcreation | Marketing slogans, emotional copy, humor — intent and feeling > literal meaning |
Identify which mode applies before starting.
Steps
1. Identify source and target
Confirm: source language, target locale (e.g. tr-TR, de-DE, not just German), content type (UI, marketing, technical, legal).
If the target locale isn't specified, ask.
Success criteria: You know the exact target audience (region + formality level).
2. First pass — literal translation
Translate accurately, preserving all meaning. Note every idiom, cultural reference, or humor that won't land in the target culture — flag with [ADAPT].
Success criteria: Nothing is lost in meaning; adaptation candidates are clearly marked.
3. Second pass — cultural adaptation
For each [ADAPT] flag:
- Replace idioms with target-culture equivalents (not literal translations)
- Adjust formality: Turkish has T/V distinction (sen/siz); German has du/Sie — match the brand voice
- Localize examples, measurements, date formats, currency
- Adapt humor: if it doesn't translate, replace with something that achieves the same effect
Success criteria: A native speaker would not identify the text as translated.
4. Technical localization (if applicable)
- Placeholder handling:
{name},%s,{{variable}}— preserve all placeholders exactly - String length: UI strings often have length constraints — flag anything that grew >20%
- RTL languages: flag if target is Arabic/Hebrew and layout changes may be needed
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.
- 5d ago First seen · 70 lines · 25 tokens per session scan A c56e1770f0c0
localization is a skill published in the GitHub repository furkangonel/cowrangler (2 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 740 once invoked, about $0.0001 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 2026-08-31.
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