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data-insights

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Aktualisiert28. April 2026 um 07:46

`/data-insights` analyzes CSV or Excel data and produces plain-English insights. Use when the user wants quick answers about targets, trends, anomalies, segments, top/bottom performers, averages, and totals.

Installation

Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.

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Quelle

giljae

giljae/enterprise-ai-skills-antigravity

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Verwandte BerufeSOC

Basierend auf der SOC-Berufsklassifikation

DatenwissenschaftlerInformatik- und Mathematikberufe·SOC 15-2051

Datei-Explorer

4 Dateien

SKILL.md

readonly

name	data-insights
version	0.1.0
description	`/data-insights` analyzes CSV or Excel data and produces plain-English insights. Use when the user wants quick answers about targets, trends, anomalies, segments, top/bottom performers, averages, and totals.
allowed-tools	["Read","Bash","AskUserQuestion"]

/data-insights

Inputs

Ask for a CSV or Excel file path if none is provided. Confirm the target column only if it is ambiguous.

Output

The script creates a 3-tab Excel output:

Summary
Full Analysis
Raw Data

Also summarize the most important findings in the chat.

Process

Install dependencies from scripts/requirements.txt if needed.
Run python scripts/analyze_data.py <file>.
Report the output file path and 3-5 key insights.

References

Read references/framework.md for the full analysis behavior and expected output.

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name	data-insights
version	0.1.0
description	`/data-insights` analyzes CSV or Excel data and produces plain-English insights. Use when the user wants quick answers about targets, trends, anomalies, segments, top/bottom performers, averages, and totals.
allowed-tools	["Read","Bash","AskUserQuestion"]

/data-insights

Inputs

Ask for a CSV or Excel file path if none is provided. Confirm the target column only if it is ambiguous.

Output

The script creates a 3-tab Excel output:

Summary
Full Analysis
Raw Data

Also summarize the most important findings in the chat.

Process

Install dependencies from scripts/requirements.txt if needed.
Run python scripts/analyze_data.py <file>.
Report the output file path and 3-5 key insights.

References

Read references/framework.md for the full analysis behavior and expected output.