データ分析
#data
data-storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
DeepseekModel
キュレーション済みスキル
品質 優秀 · 90
v1.0.0
取得
https://deepseekmodel.com/api/download.php?id=wshobson-agents-plugins-business-analytics-skills-data-storytelling-skill-md&format=skill
ダウンロード .skill
標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
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
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ダウンロードした .skill に含まれるフィールド。
| フィールド | 説明 |
|---|---|
| format | フォーマット識別子（skill/v1） |
| skill_id | スキル固有 ID |
| name | スキル名 |
| version | バージョン |
| description | 説明 |
| category | カテゴリ（配列） |
| trigger_words | トリガーワード |
| tags | タグ |
| source | ソース |
| source_url | ソース URL（本ページ） |
| exported_at | エクスポート日時（ダウンロード毎） |
| system_prompt | システムプロンプト本文 |
| model_config | モデル設定：provider / model / temperature / max_tokens / top_p |
| examples | サンプル |
| install_guide | 各プラットフォームの導入説明（Coze / Dify / Claude / カスタム） |
