data-storytelling
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- @wshobson · no license declared
- Token usage
- Lean
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- Guided setup
- External API key
- Not required
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- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
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- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: data-storytelling
description: Transform data into compelling narratives using visualization, context, and persuasive structure…
category: data
runtime: no special runtime
---
# data-storytelling output preview
## PART A: Task fit
- Use case: Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Use This Skill / Core Concepts / 1. Story Structure” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.”.
- **02** When the source has headings, the agent prioritizes “When to Use This Skill / Core Concepts / 1. Story Structure” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “When to Use This Skill / Core Concepts / 1. Story Structure”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: data-storytelling
description: Transform data into compelling narratives using visualization, context, and persuasive structure…
category: data
source: wshobson/agents
---
# data-storytelling
## When to use
- Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to Use This Skill / Core Concepts / 1. Story Structure” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "data-storytelling" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to Use This Skill / Core Concepts / 1. Story Structure
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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
Decide Fit First
Design Intent
How To Use It
Boundaries And Review