SkillsAdd

onewave-ai/claude-skills

executive-dashboard-generator

Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations.

First seen Jan 24, 2026

Installation

$ npx skills add onewave-ai/claude-skills --skill executive-dashboard-generator
View on skills.sh ↗ GitHub repository ↗

Summary

  • Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations.
  • Creates data-driven narratives for leadership.
  • Use when users need to turn spreadsheets into executive summaries or board reports.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 287
License MIT
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,208 B
  • docs SUMMARY.md 336 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 364 installs

SKILL.md

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.