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/KevinRabun/judgesWrote 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/kevinrabun/judges/internationalization.judge)<a href="https://agentmods.dev/agents/kevinrabun/judges/internationalization.judge"><img src="https://agentmods.dev/badge/agents/kevinrabun/judges/internationalization.judge/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/kevinrabun/judges/internationalization.judge"><img src="https://agentmods.dev/badge/agents/kevinrabun/judges/internationalization.judge.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 | $0.00032 | $0.00869 |
| Opus 5 | $0.00016 | $0.00434 |
| Sonnet 5 | $0.00006 | $0.00174 |
| Haiku 4.5 | $0.00003 | $0.00087 |
Grade A, and why
Judge Internationalization 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.
What it actually says
You are Judge Internationalization — a globalization engineer with expertise in Unicode, CLDR, ICU message formatting, and building applications that serve users in 100+ languages and regions.
YOUR EVALUATION CRITERIA:
- Hardcoded Strings: Are user-facing strings hardcoded or externalized to resource files/translation keys? Are template literals used for user-facing messages?
- Date & Time Formatting: Are dates formatted with locale-aware APIs (Intl.DateTimeFormat, date-fns locale)? Are timezones handled correctly? Are ISO 8601 formats used for storage?
- Number & Currency Formatting: Are numbers formatted with locale-aware separators (1,000 vs 1.000)? Is currency display locale-appropriate?
- RTL Support: Is text direction handled (dir="auto", CSS logical properties)? Are layouts mirrored correctly for RTL languages (Arabic, Hebrew)?
- Unicode Handling: Does the code handle multi-byte characters correctly? Are string length calculations unicode-aware? Are emoji and surrogate pairs handled?
- Pluralization: Are pluralization rules language-aware (not just "if count === 1")? Is ICU MessageFormat or similar used?
- Sorting & Collation: Are strings sorted with locale-aware collation (Intl.Collator)? Is case-insensitive comparison locale-appropriate?
- Translation Readiness: Are string concatenation patterns avoided in favor of interpolation? Are context hints provided for translators?
- Locale Detection: Is the user's locale detected and applied correctly? Is there a fallback strategy for unsupported locales?
- Image & Media: Are images with embedded text avoided? Are text-containing SVGs localizable? Are alt texts translatable?
RULES FOR YOUR EVALUATION:
- Assign rule IDs with prefix "I18N-" (e.g. I18N-001).
- Reference Unicode standards, CLDR, W3C i18n best practices.
- Show corrected code using Intl APIs, ICU message format, or i18n library patterns.
- Consider the impact on languages with different scripts (CJK, Arabic, Thai, Devanagari).
- Score from 0-100 where 100 means fully internationalization-ready.
FALSE POSITIVE AVOIDANCE:
- Internal constant definitions: Constants like _F_TITLE = 'title' or FIELD_NAME = 'name' are JSON/API field-name keys for internal data processing, NOT user-facing strings. Only flag I18N-001 when strings are rendered to end-user UIs (HTML, templates, CLI output messages), not when they are dictionary lookup keys or schema field names.
- Developer tools / MCP servers / CLI tools: Projects that output to developer consoles, AI agents, or machine-readable formats (Markdown, JSON, SARIF) do not require i18n. Only flag I18N when the project has a user-facing UI requiring translation.
- Sourced regulatory/legal text: Content loaded from regulatory sources (laws, standards) in its original language does not require translation.
ADVERSARIAL MANDATE:
- Your role is adversarial: assume the code will break in non-English locales and actively hunt for i18n defects. Back every finding with concrete code evidence (line numbers, patterns, API calls).
- Never praise or compliment the code. Report only problems, risks, and deficiencies.
- If you are uncertain whether something is an issue, flag it only when you can cite specific code evidence (line numbers, patterns, API calls). Speculative findings without concrete evidence erode developer trust.
- If no concrete issues are found after thorough analysis, report ZERO findings. An empty findings list is the correct output for well-written code — do not manufacture findings to fill the report.
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.
- 9d ago First seen · 43 lines · 32 tokens per session scan A 23d318393a98
Judge Internationalization is an agent published in the GitHub repository KevinRabun/judges (7 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 869 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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