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technical-to-business-translator

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フォーク3

更新日2026年6月14日 05:12

Reframe technical analysis findings in business language. Activate when findings need to reach a non-technical audience, when jargon is obscuring the message, or when a stakeholder needs to understand and act on statistical results without a technical background.

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ryudkiss-hue

ryudkiss-hue/nyc_data

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When to use

Delivering analysis results to a VP, C-suite, or business team without data backgrounds
A technical report needs a plain-language executive version
Statistical output (p-values, confidence intervals, model metrics) needs business translation
A dashboard explanation needs to be written for non-technical users

Process

Detect and list jargon — run scripts/jargon_detector.py to flag technical terms; score reading level against grade-10 target
Match audience persona — identify the audience type (executive, product manager, finance, ops) and their known priorities using references/audience_personas.md
Apply translation patterns — replace jargon using references/translation_patterns.md (e.g. "statistically significant at p < 0.05" → "we're 95% confident this result is real, not random"); use metaphor bank for complex concepts
Rewrite for business framing — restructure findings around business outcomes: revenue, cost, risk, customer impact. Lead with the implication, not the method.
Review readability — re-run scripts/jargon_detector.py on the translated version; verify grade-10 readability and no residual jargon
Produce dual output — generate a plain-language version alongside the original technical version for reference

Inputs the skill needs

Required: the technical text, findings, or report to translate
Required: target audience (role and technical comfort level)
Optional: business priorities or context of the audience
Optional: decisions the audience needs to make based on the findings

Output

Jargon report with flagged terms and suggested replacements
Before/after readability scores
Dual-version document: translated business language + original technical version

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name	technical-to-business-translator
description	Reframe technical analysis findings in business language. Activate when findings need to reach a non-technical audience, when jargon is obscuring the message, or when a stakeholder needs to understand and act on statistical results without a technical background.

When to use

Delivering analysis results to a VP, C-suite, or business team without data backgrounds
A technical report needs a plain-language executive version
Statistical output (p-values, confidence intervals, model metrics) needs business translation
A dashboard explanation needs to be written for non-technical users

Process

Detect and list jargon — run scripts/jargon_detector.py to flag technical terms; score reading level against grade-10 target
Match audience persona — identify the audience type (executive, product manager, finance, ops) and their known priorities using references/audience_personas.md
Apply translation patterns — replace jargon using references/translation_patterns.md (e.g. "statistically significant at p < 0.05" → "we're 95% confident this result is real, not random"); use metaphor bank for complex concepts
Rewrite for business framing — restructure findings around business outcomes: revenue, cost, risk, customer impact. Lead with the implication, not the method.
Review readability — re-run scripts/jargon_detector.py on the translated version; verify grade-10 readability and no residual jargon
Produce dual output — generate a plain-language version alongside the original technical version for reference

Inputs the skill needs

Required: the technical text, findings, or report to translate
Required: target audience (role and technical comfort level)
Optional: business priorities or context of the audience
Optional: decisions the audience needs to make based on the findings

Output

Jargon report with flagged terms and suggested replacements
Before/after readability scores
Dual-version document: translated business language + original technical version