technical-to-business-translator
When to use
When technical output (model results, statistical tests, query findings) needs to be understood by a business audience. Also use to review your own writing before sending — it is easy to slip into jargon without noticing.
Process
- Detect jargon — run
scripts/jargon_detector.pyon the draft text to flag technical terms that need translation. - Score readability — run
scripts/readability_scorer.pyto get Flesch-Kincaid grade level and sentence complexity metrics; target ≤ grade 10 for executive audiences. - Identify the audience persona — use
references/stakeholder_personas.mdto select the persona that best matches your reader; each persona has vocabulary preferences and typical questions. - Apply translation patterns — use
references/translation_pattern_library.mdto swap technical language for business equivalents (e.g., "p-value < 0.05" → "we're 95% confident this isn't random chance"). - Replace with metaphors where needed — for complex statistical concepts, pick an appropriate metaphor from
references/metaphor_bank.md. - Draft the translated version — use
assets/translation_template.mdto produce the parallel technical/business version; keep the original in an appendix for technical reviewers.
Inputs the skill needs
- Draft technical text or findings
- Target audience role (VP, product manager, operations, finance, etc.)
Output
- Jargon detection report
- Readability score before/after
- Translated text with original in appendix (
translation_template.md)
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