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 mojavestudio/Pela-Translate --skill pela-en-jpgit clone --depth 1 https://github.com/mojavestudio/Pela-TranslateWrote 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/mojavestudio/pela-translate/pela-en-jp)<a href="https://agentmods.dev/skills/mojavestudio/pela-translate/pela-en-jp"><img src="https://agentmods.dev/badge/skills/mojavestudio/pela-translate/pela-en-jp/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/mojavestudio/pela-translate/pela-en-jp"><img src="https://agentmods.dev/badge/skills/mojavestudio/pela-translate/pela-en-jp.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 | $0.00059 | $0.00681 |
| Opus 5 | $0.00030 | $0.00341 |
| Sonnet 5 | $0.00012 | $0.00136 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
pela-en-jp 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 11d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Translation tuning: English → Japanese
Invoked as /pela:en-jp [tone] [script]. Both args are optional and order-independent.
tone: one ofneutral(default),friendly,formal,casualscript: one ofdefault(default),kanaonly,kanjionly,romaji
Parse args for these two values (case-insensitive, any order, either or both omitted). If a token doesn't match either list, ignore it rather than erroring — treat unmatched input as ordinary user context to consider alongside the translation.
Naturalness
- Prefer a natural equivalent over a literal transliteration. A short greeting or filler word transliterated straight into katakana usually reads as foreign or lazy to a native speaker, even when it isn't technically wrong.
- When the source is casual or spoken, match register with equally casual native phrasing rather than a textbook-formal one.
- Loanwords already naturalized into the target language (brand names, established katakana vocabulary) are fine to keep as loanwords. The rule is about avoiding gratuitous transliteration of ordinary words that already have a native equivalent, not banning loanwords outright.
Tone
- neutral: Balanced, unmarked register — neither noticeably formal nor noticeably casual.
- friendly: Warm, approachable phrasing. Contractions and casual connectors are fine where natural.
- formal: Polite, professional register (keigo-appropriate where relevant). Avoid casual connectors and slang.
- casual: Relaxed, conversational register, the way you'd address someone you know well.
Apply whichever tone was parsed from args (default neutral) to the translation.
Script
Apply only if a script arg was parsed; otherwise use standard mixed orthography.
- kanaonly: Render all target text in kana only — no kanji. Prefer hiragana for native vocabulary and grammar; katakana only for genuine loanwords.
- kanjionly: Use standard mixed kanji/kana orthography the way a fluent native speaker would — do not artificially avoid kanji. (Functionally the same as the default; useful when the caller wants to be explicit.)
- romaji: Transliterate the target text into the Latin alphabet using a standard romanization system. Name the system (e.g. Hepburn) if more than one is plausible for the content.
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.
- 11d ago First seen · 45 lines · 59 tokens per session scan A 09a858fc1a23
pela-en-jp is a skill published in the GitHub repository mojavestudio/Pela-Translate (0 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 681 once invoked, about $0.0003 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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