data-storytelling
用視覺化、脈絡和有說服力的結構，把資料變成能推動決策的敘事
中文翻譯
--- name: data-storytelling description: 運用視覺化、脈絡和有說服力的結構，把資料轉成引人入勝的敘事。向利害關係人簡報分析結果、製作資料報告，或建構高階主管簡報時使用。 --- # 資料說故事 把原始資料轉成能推動決策、激發行動的引人入勝的敘事。 ## 何時使用這個 Skill - 向高階主管簡報分析結果 - 製作季度業務檢討 - 建構投資人簡報 - 撰寫以資料為依據的報告 - 向非技術背景的聽眾傳達洞察 - 根據資料提出建議 ## 核心概念 ### 1. 故事結構 ``` Setup → Conflict → Resolution Setup: Context and baseline Conflict: The problem or opportunity Resolution: Insights and recommendations ``` ### 2. 敘事弧線 ``` 1. Hook: Grab attention with surprising insight 2. Context: Establish the baseline 3. Rising Action: Build through data points 4. Climax: The key insight 5. Resolution: Recommendations 6. Call to Action: Next steps ``` ### 3. 三大支柱 | 支柱 | 目的 | 組成 | | ------------- | -------- | -------------------------------- | | **Data** | 證據 | 數字、趨勢、比較 | | **Narrative** | 意義 | 脈絡、因果、影響 | | **Visuals** | 清晰 | 圖表、圖解、重點標示 | ## 詳細模式與實作範例 詳細的模式文件放在 `references/details.md`。上面的導覽層不夠用時，再讀那個檔案。 ## 最佳實務 ### 該做的 - **從「so what」開始** - 以洞察領頭 - **用三的法則** - 三個重點、三個比較 - **用展示，不要用說的** - 讓資料說話 - **讓它跟個人有關** - 連結到聽眾的目標 - **以行動作結** - 清楚的下一步 ### 不該做的 - **不要倒資料** - 嚴格地挑選 - **不要把洞察藏起來** - 把關鍵發現放前面 - **不要用行話** - 配合聽眾的用詞 - **不要先講方法論** - 先講脈絡，再講方法 - **不要忘了敘事** - 數字需要意義
英文原文
--- name: data-storytelling description: Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations. --- # Data Storytelling Transform raw data into compelling narratives that drive decisions and inspire action. ## When to Use This Skill - Presenting analytics to executives - Creating quarterly business reviews - Building investor presentations - Writing data-driven reports - Communicating insights to non-technical audiences - Making recommendations based on data ## Core Concepts ### 1. Story Structure ``` Setup → Conflict → Resolution Setup: Context and baseline Conflict: The problem or opportunity Resolution: Insights and recommendations ``` ### 2. Narrative Arc ``` 1. Hook: Grab attention with surprising insight 2. Context: Establish the baseline 3. Rising Action: Build through data points 4. Climax: The key insight 5. Resolution: Recommendations 6. Call to Action: Next steps ``` ### 3. Three Pillars | Pillar | Purpose | Components | | ------------- | -------- | -------------------------------- | | **Data** | Evidence | Numbers, trends, comparisons | | **Narrative** | Meaning | Context, causation, implications | | **Visuals** | Clarity | Charts, diagrams, highlights | ## Detailed patterns and worked examples Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient. ## Best Practices ### Do's - **Start with the "so what"** - Lead with insight - **Use the rule of three** - Three points, three comparisons - **Show, don't tell** - Let data speak - **Make it personal** - Connect to audience goals - **End with action** - Clear next steps ### Don'ts - **Don't data dump** - Curate ruthlessly - **Don't bury the insight** - Front-load key findings - **Don't use jargon** - Match audience vocabulary - **Don't show methodology first** - Context, then method - **Don't forget the narrative** - Numbers need meaning