home / skills / jeremylongshore / claude-code-plugins-plus-skills / data-story-outliner

data-story-outliner skill

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/skills/12-data-analytics/data-story-outliner

This skill helps automate data story outliner tasks with step-by-step guidance, production-ready code, and validation against standards.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill data-story-outliner

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: "data-story-outliner"
description: |
  Process data story outliner operations. Auto-activating skill for Data Analytics.
  Triggers on: data story outliner, data story outliner
  Part of the Data Analytics skill category. Use when working with data story outliner functionality. Trigger with phrases like "data story outliner", "data outliner", "data".
allowed-tools: "Read, Write, Edit, Bash(cmd:*), Grep"
version: 1.0.0
license: MIT
author: "Jeremy Longshore <[email protected]>"
---

# Data Story Outliner

## Overview

This skill provides automated assistance for data story outliner tasks within the Data Analytics domain.

## When to Use

This skill activates automatically when you:
- Mention "data story outliner" in your request
- Ask about data story outliner patterns or best practices
- Need help with data analytics skills covering sql queries, data visualization, statistical analysis, and business intelligence.

## Instructions

1. Provides step-by-step guidance for data story outliner
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards

## Examples

**Example: Basic Usage**
Request: "Help me with data story outliner"
Result: Provides step-by-step guidance and generates appropriate configurations


## Prerequisites

- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of data analytics concepts


## Output

- Generated configurations and code
- Best practice recommendations
- Validation results


## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |


## Resources

- Official documentation for related tools
- Best practices guides
- Community examples and tutorials

## Related Skills

Part of the **Data Analytics** skill category.
Tags: sql, analytics, visualization, statistics, bi

Overview

This skill automates data story outliner tasks for the Data Analytics workflow. It helps structure insights, sequence analysis steps, and produce reproducible artifacts like SQL snippets, visualization specs, and narrative outlines. Use it to turn raw analysis steps into a clear, actionable story for stakeholders.

How this skill works

The skill inspects your request for data story outliner triggers and context, then generates a step-by-step outline tailored to the dataset, analytic goal, and audience. It can produce code snippets (SQL, Python), visualization recommendations (chart types and specs), and validation checks to ensure outputs meet common standards. Outputs are formatted for immediate use in notebooks, dashboards, or reports.

When to use it

You need a clear sequence of analysis steps for a dataset or BI report.
Preparing a narrative for stakeholders from analytic results.
Designing visuals and captions to communicate key findings.
Generating reproducible analysis artifacts (SQL, Python snippets, viz specs).
Validating that story components follow analytics best practices.

Best practices

Start with a concise question or hypothesis to focus the outline.
Specify dataset schema and sample rows to get precise code recommendations.
Request target audience and delivery format (slide, report, dashboard) for tailored narratives.
Ask for validation checks and thresholds to include in the outline.
Iterate: run generated snippets, provide outputs back to refine the story.

Example use cases

Outline a data story showing sales trends and drivers, with SQL queries and visualization specs.
Convert exploratory notebook steps into a stakeholder-ready slide deck outline.
Generate a reproducible sequence: data prep, modeling summary, metrics, and suggested visuals.
Validate a BI dashboard plan: required KPIs, filters, slices, and expected data quality checks.
Create a communication plan for releasing analytic results to executives and product teams.

FAQ

What inputs should I provide for best results?

Provide the business question, dataset schema or sample rows, target audience, and desired output format (report, dashboard, slide deck).

Does it produce production-ready code?

It generates production-oriented snippets and configurations, but you should review and adapt them to your environment, credentials, and data access patterns.