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data-analyst

Ingest CSV, Excel, or JSON files and analyze them with SQL to produce dashboards, reports, or datasets.

Updated May 25, 2026
Search Tags:#data#dashboard#sql#report#analyze#ingest
One-click install
npx skills add https://github.com/cmetech/otto-cli --skill data-analyst-cmetech
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analyst
Source: https://github.com/cmetech/otto-cli/tree/main/src/resources/extensions/analyst/skill
Command: npx skills add https://github.com/cmetech/otto-cli --skill data-analyst-cmetech

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Retrieve, analyze, summarize, or report on data files by performing a real-data workflow instead of relying on memory. It drives an ingest -> SQL analysis -> deliverable workflow to produce dashboards, written reports, or cleaned datasets.

Core Features & Use Cases

  • Ingest data files to reveal schema and sample data.
  • Analyze with SQL against the ingested table using the scratchpad tool; prefer aggregations over raw rows.
  • Deliverables include dashboards (html-app), reports (document), or datasets (csv/parquet), written to /deliverables.

Quick Start

Ingest a data file by providing its absolute path, then request an analysis to produce a dashboard, report, or cleaned dataset.

Frequently Asked Questions about data-analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze CSV or Excel files using SQL to generate a report?▼

To analyze CSV or Excel files using SQL, ingest the data file by providing its absolute path, run SQL aggregations against the ingested table, and output a report.md or dataset file to the deliverables directory.

Can I create an interactive dashboard from raw JSON data?▼

Yes, you can create an interactive dashboard from raw JSON data by ingesting the JSON file, performing SQL-based analysis on the revealed schema, and generating a dashboard.html file as the final deliverable.

What's the best way to run data quality checks on a spreadsheet without manual formulas?▼

Running data quality checks on a spreadsheet without manual formulas is best done by ingesting the file into a SQL table, querying for anomalies and summaries, and exporting the validated results as a cleaned dataset.

Do I need to predefine a database schema before analyzing my data files?▼

No, you do not need to predefine a database schema before analyzing data files. The ingestion process automatically reveals the schema and sample data, allowing you to immediately run SQL queries for trends and summaries.

Why does my SQL data analysis workflow prefer aggregations over raw rows?▼

Your SQL data analysis workflow prefers aggregations over raw rows to optimize decision support, ensuring the generated dashboards and reports highlight meaningful trends and summaries rather than overwhelming raw data outputs.

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