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 indranilbanerjee/digital-marketing-pro --skill multilingual-scoregit clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-proWrote 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/indranilbanerjee/digital-marketing-pro/multilingual-score)<a href="https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/multilingual-score"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/multilingual-score/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/indranilbanerjee/digital-marketing-pro/multilingual-score"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/multilingual-score.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 | $0.00173 | $0.02449 |
| Opus 5 | $0.00086 | $0.01224 |
| Sonnet 5 | $0.00035 | $0.00490 |
| Haiku 4.5 | $0.00017 | $0.00245 |
Grade A, and why
multilingual-score 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 4d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/digital-marketing-pro:multilingual-score
Purpose
Score translated or localized content across multiple quality dimensions to determine whether it is ready for publishing, needs native speaker review, or requires re-translation. Combines technical translation scoring (length ratios, formatting preservation, placeholder integrity, key term consistency) with content quality evaluation, brand voice consistency checking, and market-specific compliance verification into a single composite multilingual quality score.
Use this command after any translation or localization workflow to validate quality before content goes live. It replaces subjective "looks good" assessments with a structured, repeatable scoring methodology that catches issues automated translation often introduces — brand voice drift, formatting damage, missing do-not-translate terms, compliance gaps in the target market, and length distortion that signals missing or added content. The composite score provides a clear publish/review/re-translate classification so the team knows exactly what action to take.
Input Required
The user must provide (or will be prompted for):
- Original content: The source text that was translated — provided as inline text, a file path, or a URL to the source content. This serves as the reference for translation accuracy scoring. Required for technical translation scoring; if omitted, only content quality, brand voice, and compliance dimensions are scored
- Translated content: The translated or localized text to score — provided as inline text, a file path, or a URL. This is the primary content being evaluated. Required
- Source language: The language code of the original content (e.g.,
en-US,en-GB,de-DE). Defaults to the brand's primary language from the language configuration if not specified - Target language: The language code of the translated content (e.g.,
de-DE,fr-FR,hi-IN,ja-JP). Required — determines which compliance rules apply and which translation service benchmarks to reference - Do-not-translate terms (optional): Specific terms that must appear unchanged in the translation. Defaults to the brand profile's
language.do_not_translatelist. Additional terms can be provided to supplement the brand list for this specific scoring run - Content type (optional): The type of content being scored —
blog,email,ad,landing_page,social,product_description,legal,technical. Affects content quality scoring weights and brand voice expectations. Defaults to auto-detection based on content structure
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.
- 4d ago First seen · 53 lines · 173 tokens per session scan A 79bfe7aef203
multilingual-score is a skill published in the GitHub repository indranilbanerjee/digital-marketing-pro (806 stars, last pushed 4d ago), licensed MIT. It adds 173 tokens to every session and 2,449 once invoked, about $0.0009 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 2026-09-07.
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