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 Dragoon0x/taste-skills --skill audience-translationgit clone --depth 1 https://github.com/Dragoon0x/taste-skillsWrote 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/dragoon0x/taste-skills/audience-translation)<a href="https://agentmods.dev/skills/dragoon0x/taste-skills/audience-translation"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/audience-translation/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/dragoon0x/taste-skills/audience-translation"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/audience-translation.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 | $0.00044 | $0.00238 |
| Opus 5.5 | $0.00018 | $0.00095 |
| Sonnet 5.5 | $0.00009 | $0.00048 |
| Haiku 4.5 | $0.00004 | $0.00024 |
Grade A, and why
audience-translation 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
Audience Translation
Same observation. Three languages. All accurate.
How to use
/audience-translationTranslate design feedback for multiple audiences in this conversation.
Constraints
Three Translations
- MUST provide the same observation in three forms:
- To designers: Precise technical language (visual weight, hierarchy, density, rhythm)
- To developers: Implementation-mapped language (z-index, opacity, spacing tokens, contrast ratios)
- To stakeholders: Outcome-connected language (user behavior, conversion, trust, comprehension)
- All three MUST describe the same underlying observation
- NEVER dumb down for stakeholders. Simplify, but stay accurate.
Anti-Patterns
- Using designer jargon with developers and expecting understanding
- Using developer jargon with stakeholders and expecting buy-in
- Oversimplifying so much that the nuance is lost
- Translating condescendingly ("to put it simply...")
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 · 29 lines · 44 tokens per session scan A 7b16d345d27a
audience-translation is a skill published in the GitHub repository Dragoon0x/taste-skills (7 stars, last pushed 8mo ago), licensed MIT. It adds 44 tokens to every session and 238 once invoked, about $0.0002 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 2026-08-31.
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