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 reem-sab/tech-writer-prompts --skill localization-prepgit clone --depth 1 https://github.com/reem-sab/tech-writer-promptsWrote 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/reem-sab/tech-writer-prompts/localization-prep)<a href="https://agentmods.dev/skills/reem-sab/tech-writer-prompts/localization-prep"><img src="https://agentmods.dev/badge/skills/reem-sab/tech-writer-prompts/localization-prep/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/reem-sab/tech-writer-prompts/localization-prep"><img src="https://agentmods.dev/badge/skills/reem-sab/tech-writer-prompts/localization-prep.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 | $0.00095 | $0.00778 |
| Opus 5 | $0.00048 | $0.00389 |
| Sonnet 5 | $0.00019 | $0.00156 |
| Haiku 4.5 | $0.00010 | $0.00078 |
Grade A, and why
localization-prep 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Localization Prep
Flags idioms, cultural references, ambiguous antecedents, and merged sentences that tend to break or distort in translation, and suggests a neutral, literal-translation-friendly rewrite for each. Run it before a page goes to a translation team or pipeline.
Inputs
{{DRAFT}}: The draft text to prepare for translation.
How to apply
Substitute each {{PLACEHOLDER}} above with the user's actual content, then
follow the prompt below exactly — including its output format and its stated
limits.
You are preparing DRAFT for translation. A translator (or a translation model) working sentence by sentence, without the cultural or product context you have, will hit specific failure points. Find them before they find your translation team.
What to flag
- Idioms — figurative phrases that don't survive literal translation ("under the hood," "out of the box," "a ballpark figure," "hit the ground running"). A translator either mistranslates these literally or has to guess the intended meaning.
- Cultural references — sports metaphors, holiday references, or region-specific analogies that assume shared context a reader in another culture won't have ("like a Hail Mary pass," "Black Friday pricing," "as American as apple pie").
- Ambiguous antecedents — a pronoun or reference where the noun it refers to isn't unambiguous from the immediate sentence alone. This matters more for translation than for a native English reader, because many target languages require choosing a gender, number, or case for the referent — an ambiguous "it" in English forces the translator to guess which noun to agree with.
- Merged sentences — a single sentence carrying more than one instruction or claim, joined by "and," "which," or a comma splice. These are more likely to be mistranslated or split incorrectly, and should be broken into separate sentences even though the meaning is already clear to an English reader.
What ships with it
4 files 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.
- 9d ago First seen · 82 lines · 95 tokens per session scan A a605dc4d55e7
localization-prep is a skill published in the GitHub repository reem-sab/tech-writer-prompts (4 stars, last pushed 10d ago), licensed MIT. It adds 95 tokens to every session and 778 once invoked, about $0.0005 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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