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executive-dashboard-generator

executive-dashboard-generator

github.com/onewave-aiData & databases393413 installsUpdated 1w ago
Repository

About executive-dashboard-generator

Executive Dashboard Generator turns business data into an executive-facing dashboard with visualizations, findings, and recommendations. It guides users from data discovery and analysis through report assembly across financial, sales and marketing, operations, and customer domains.

Key features

  1. 01Examines data structure and quality
  2. 02Analyzes trends, changes, and outliers
  3. 03Connects metrics to business outcomes
  4. 04Selects executive-focused visualizations
  5. 05Builds a report with recommendations

Use cases

  1. 01Summarizing financial or sales data for executives
  2. 02Identifying operational trends and anomalies
  3. 03Turning customer metrics into action recommendations

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/onewave-ai/claude-skills --skill executive-dashboard-generator

After installing, type/executive-dashboard-generatorin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
analysis-coverage.md
best-practices.md
output-template.md

Details

From the project README

Executive Dashboard Generator

Turn raw data into executive-ready insights with visualizations and recommendations.

Contents

  • references/analysis-coverage.md — supported data inputs and analysis types per domain (financial, sales/marketing, operations, customer).
  • references/output-template.md — the full Markdown dashboard template to populate.
  • references/best-practices.md — reporting principles, visualization do/don't, trigger phrases, example request.

Workflow

  1. Clarify business context and collect the data sources (files, Sheets links, query output). See references/analysis-coverage.md for accepted inputs and the analysis types to run per domain.
  2. Discover the data: identify structure, date ranges, granularity, key metrics and dimensions, and any data quality issues. Map relationships across datasets.
  3. Analyze: calculate period-over-period changes, identify trends and patterns, flag outliers and anomalies, run cohort analysis, and set benchmarks and targets.
  4. Generate insights: synthesize findings into key messages, prioritize by business impact, connect each metric to a business outcome, and develop concrete action recommendations and risk/opportunity flags.
  5. Choose visualizations: select chart types built for executive readability and maintain a clear visual hierarchy. See references/best-practices.md for the visualization do/don't list.
  6. Assemble the report using the structure in references/output-template.md. Replace every placeholder with real values; never ship a template with bracketed placeholders left in.
  7. Prioritize recommendations and include scenario planning and a risk assessment, then deliver the dashboard.

Lead with insights over raw numbers, and answer "So what?" and "What should we do?" Apply the reporting principles in references/best-practices.md.

Comments

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