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 malue-ai/dazee-small --skill locale-aware-formattergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/locale-aware-formatter)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/locale-aware-formatter"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/locale-aware-formatter/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/malue-ai/dazee-small/locale-aware-formatter"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/locale-aware-formatter.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 | $0.00036 | $0.00776 |
| Opus 5 | $0.00018 | $0.00388 |
| Sonnet 5 | $0.00007 | $0.00155 |
| Haiku 4.5 | $0.00004 | $0.00078 |
Grade A, and why
locale-aware-formatter 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 10d 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.
What it actually says
文化自适应格式化
根据语言和文化环境自动适配文档格式：日期格式、货币符号、信函样式、数字分隔符、称谓礼仪。
使用场景
- 用户说「帮我写一封商务信」→ 自动适配对应语言的信函格式
- 用户说「格式化这份报告」→ 日期、数字、货币按用户 locale 呈现
- 用户说「把这个文档转成正式格式」→ 适配对应文化的正式规范
执行方式
通过 LLM 结合系统 locale 检测，自动适配文化规范。
Locale 检测
# 检测系统语言设置
echo $LANG
# macOS 额外检测
defaults read NSGlobalDomain AppleLanguages 2>/dev/null
格式适配规则
日期格式
| Locale | 格式 | 示例 |
|---|---|---|
| en-US | MM/DD/YYYY | 02/09/2026 |
| en-GB | DD/MM/YYYY | 09/02/2026 |
| zh-CN | YYYY年MM月DD日 | 2026年02月09日 |
| ja-JP | YYYY年MM月DD日 | 2026年02月09日 |
| de-DE | DD.MM.YYYY | 09.02.2026 |
数字与货币
| Locale | 千位分隔 | 小数点 | 货币 |
|---|---|---|---|
| en-US | 1,000.00 | . | $1,000.00 |
| de-DE | 1.000,00 | , | 1.000,00 € |
| zh-CN | 1,000.00 | . | ¥1,000.00 |
| ja-JP | 1,000 | . | ¥1,000 |
商务信函格式
English (formal):
Dear Mr./Ms. [Last Name],
[Body]
Sincerely,
[Full Name]
[Title]
中文（正式）:
[职务] [姓名] ：
[正文]
此致
敬礼
[署名]
[日期]
日本語（敬語）:
[会社名]
[部署名] [役職] [名前] 様
[本文]
敬具
[署名]
[日付]
称谓礼仪
| 文化 | 规范 |
|---|---|
| English | Mr./Ms./Dr. + Last Name（首次），First Name（熟悉后） |
| 中文 | 姓 + 职务（王总、李经理），或 姓 + 先生/女士 |
| 日本語 | 姓 + 様/さん，职务时 姓 + 役職 |
| 한국어 | 성 + 님/씨 |
输出规范
- 自动检测对话语言，适配格式
- 如检测到 OS locale 与对话语言不同，询问用户偏好
- 保持核心内容不变，只调整格式和礼仪层
- 不强制转换——用户明确指定格式时优先用户要求
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.
- 10d ago First seen · 110 lines · 36 tokens per session scan A 9b99301534dc
locale-aware-formatter is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 776 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 2026-08-31.
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