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 Fu-Jie/openwebui-extensions --skill i18n-validatorgit clone --depth 1 https://github.com/Fu-Jie/openwebui-extensionsWrote 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/fu-jie/openwebui-extensions/i18n-validator)<a href="https://agentmods.dev/skills/fu-jie/openwebui-extensions/i18n-validator"><img src="https://agentmods.dev/badge/skills/fu-jie/openwebui-extensions/i18n-validator/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/fu-jie/openwebui-extensions/i18n-validator"><img src="https://agentmods.dev/badge/skills/fu-jie/openwebui-extensions/i18n-validator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00035 | $0.00107 |
| Opus 5.5 | $0.00014 | $0.00043 |
| Sonnet 5.5 | $0.00007 | $0.00021 |
| Haiku 4.5 | $0.00003 | $0.00011 |
Grade A, and why
i18n-validator 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 2mo 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
I18n Validator
Overview
Ensures all 12 supported languages (en-US, zh-CN, etc.) have aligned translation keys.
Features
- Detects missing keys in non-English dictionaries.
- Suggests translations using the core AI engine.
- Validates the
fallback_mapfor variant redirects.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 15 lines · 35 tokens per session scan A df9a3f4c690b
i18n-validator is a skill published in the GitHub repository Fu-Jie/openwebui-extensions (328 stars, last pushed 20d ago), licensed MIT. It adds 35 tokens to every session and 107 once invoked, about $0.0001 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.
Other skills, from other repositories
i18n-validate
Validate translation completeness and consistency across all locale files — detect missing keys, untranslated strings, format mismatches, and glossary violations.
agent-state-bar
A design guide for an agent status bar: a short, automatically updated summary of progress, remaining tasks, tool counts, errors, and system state placed near the latest model input.
bad-case-to-dpo
A guide to turning failed production agent runs into training and evaluation data. It explains how to find the first mistake, create preference examples for DPO (Direct Preference Optimization), and check that a fix does not damage other tasks.
knowledge-org
A guide to organising large bodies of knowledge so an AI system can navigate relationships, summaries, and layers instead of searching only flat text chunks. It covers tree indexes, knowledge graphs, file-like structures, incremental updates, and long-term memory layouts.
gsd-eval-review
Audit an executed AI phase's evaluation coverage and produce an EVAL-REVIEW.md remediation plan.
gsd-validate-phase
Retroactively audit and fill Nyquist validation gaps for a completed phase.