Skip to content
Automation
Skill

/science-communication

Translating technical findings for non-technical audiences. Narrative frameworks (Pyramid Principle, SCQA), plain-language translation, executive summaries, policy briefs, causal language. Use when presenting to stakeholders or reviewing deliverables

From plugin
auto-empirical-research-skills
3.3k200 skills146 agents
Install
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill science-communication --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/science-communication

Context preview

The summary Claude sees to decide when to auto-load this skill.

Translating technical findings for non-technical audiences. Narrative frameworks (Pyramid Principle, SCQA), plain-language translation, executive summaries, policy briefs, causal language. Use when presenting to stakeholders or reviewing deliverables

SKILL.md

science-communication.SKILL.md
name: science-communication
description: >-
  Translating technical findings for non-technical audiences. Narrative frameworks (Pyramid Principle, SCQA), plain-language translation, executive summaries, policy briefs, causal language. Use when presenting to stakeholders or reviewing deliverables
metadata:
  audience: research-writers
  domain: research-communication

Science Communication

Translating technical data science findings for non-technical audiences. Covers audience analysis, narrative frameworks (Pyramid Principle, SCQA, AIDA), plain-language translation, executive summaries, policy briefs, causal language guidance, hedging and uncertainty communication, and accessibility standards. Complements data-scientist visualization references — handles what story to tell and to whom, not how to build charts. Use when presenting findings to stakeholders, writing executive summaries or policy briefs, communicating statistical results to non-statisticians, or reviewing a draft deliverable for clarity and audience fit.

Guidance for translating rigorous data science work into clear, compelling communication for non-technical audiences. This skill is **additive** to data-scientist's visualization references — it covers *what story the chart tells and to whom*, not *how to build the chart*.

**Boundary with data-scientist:** The data-scientist skill handles chart construction, encoding, color palettes, and export standards. This skill handles audience adaptation, narrative structure, plain-language translation, deliverable formatting, and communication quality review.

How to Use This Skill

Reference File Structure

| File | Purpose | When to Read | |------|---------|--------------| | `audience-analysis.md` | Five audience types with strategy tables | Identifying who you're writing for | | `narrative-frameworks.md` | Six narrative structures with selection guide | Choosing how to structure your story | | `plain-language.md` | Jargon translation, hedging, uncertainty, causal language | Writing findings in accessible language | | `deliverable-templates.md` | Executive summary, policy brief, presentation, talking points | Formatting a specific deliverable type | | `communication-review.md` | 10-point checklist, common pitfalls, seven deadly sins | Reviewing a deliverable before finalization | | `accessibility-equity.md` | WCAG standards, people-first language, equity-aware framing | Ensuring inclusive, accessible communication |

Reading Order

1. **Writing a report or brief?** Start with `audience-analysis.md`, then `narrative-frameworks.md`, then `deliverable-templates.md` 2. **Translating technical findings?** Read `plain-language.md` first 3. **Reviewing a draft?** Go straight to `communication-review.md` 4. **Concerned about equity or accessibility?** Read `accessibility-equity.md`

Quick Decision Trees

"Who am I writing for?"

Identifying your audience?
├─ Academic researchers or peer reviewers
│   └─ ./references/audience-analysis.md (Academic section)
├─ Policymakers or legislative staff
│   └─ ./references/audience-analysis.md (Policy section)
├─ Executives or board members
│   └─ ./references/audience-analysis.md (Executive section)
├─ General public or community members
│   └─ ./references/audience-analysis.md (Public section)
├─ Journalists or media
│   └─ ./references/audience-analysis.md (Media section)
└─ Mixed or unclear audience
    └─ ./references/audience-analysis.md (Assessment checklist)

"How should I structure this?"

Choosing a narrative structure?
├─ Need to deliver a recommendation quickly
│   └─ Pyramid Principle → ./references/narrative-frameworks.md
├─ Framing a problem that needs solving
│   └─ SCQA → ./references/narrative-frameworks.md
├─ Walking through a discovery journey
│   └─ Three-Act Data Story → ./references/narrative-frameworks.md
├─ Translating findings into action
│   └─ "So What?" Framework → ./references/narrative-frameworks.md
├─ Presenting data with narrative and visuals together
│   └─ Data-Narrative-Visual Triad → ./references/narrative-frameworks.md
├─ Persuading stakeholders to act
│   └─ AIDA → ./references/narrative-frameworks.md
└─ Not sure which to use
    └─ Selection guide table → ./references/narrative-frameworks.md

"How do I say this in plain language?"

Translating technical language?
├─ Statistical jargon (p-value, confidence interval, etc.)
│   └─ Jargon translation table → ./references/plain-language.md
├─ Expressing how certain you are
│   └─ Hedging language scale → ./references/plain-language.md
├─ Using calibrated uncertainty terms
│   └─ IPCC uncertainty framework → ./references/plain-language.md
├─ Describing causal vs correlational findings
│   └─ Causal language guide → ./references/plain-language.md
├─ General readability improvement
│   └─ Reading level guidance → ./references/plain-language.md
└─ Replacing formal/bureaucratic words
    └─ Word replacement list → ./references/plain-language.md

"What format should this take?"

Choosing a deliverable format?
├─ One-page summary for decision makers
│   └─ Executive summary → ./references/deliverable-templates.md
├─ Informing policy decisions
│   └─ Policy brief → ./references/deliverable-templates.md
├─ Presenting to a room
│   └─ Stakeholder presentation → ./references/deliverable-templates.md
├─ Talking to a journalist
│   └─ Media talking points → ./references/deliverable-templates.md
└─ Full research report
    └─ (Use REPORT_TEMPLATE.md from agent_reference/)

"Is this ready to share?"

Reviewing before finalization?
├─ Comprehensive quality check
│   └─ 10-point checklist → ./references/communication-review.md
├─ Statistical interpretation errors
│   └─ Seven deadly sins → ./references/communication-review.md
├─ Common communication pitfalls
│   └─ Pitfall catalog → ./references/communication-review.md
├─ Accessibility compliance
│   └─ WCAG checklist → ./references/accessibility-equity
Read more
Ships withauto-empirical-research-skills

📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |

Get the whole plugin