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Data Extraction

Extract and normalize data from CSV, JSON, text, Notion, and Google Drive sources.

18|7|Updated Mar 11, 2026
Search Tags:#data extraction#json#notion#csv#data normalization#google drive#data wrangling
One-click install
npx skills add https://github.com/thecloudtips/founder-os --skill data-extraction-thecloudtips
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Data Extraction
Source: https://github.com/thecloudtips/founder-os/tree/main/plugin/skills/report/data-extraction
Command: npx skills add https://github.com/thecloudtips/founder-os --skill data-extraction-thecloudtips

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex and time-consuming process of extracting, cleaning, and normalizing data from diverse sources, ensuring it's ready for immediate analysis.

Core Features & Use Cases

  • Universal Data Ingestion: Extracts data from CSV, JSON, plain text files, Notion databases, and Google Drive documents.
  • Intelligent Parsing: Automatically detects delimiters, encodings, headers, and infers data types for robust extraction.
  • Data Normalization: Standardizes column names and values across all sources into a unified schema.
  • Use Case: Consolidate customer feedback from a CSV export, a Notion database, and a Google Doc into a single, analysis-ready dataset for sentiment analysis.

Quick Start

Use the Data Extraction skill to load and normalize data from the file 'customer_feedback.csv' and the Notion database 'User Surveys'.

Frequently Asked Questions about Data Extraction

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

FAQPage Schema
How do I normalize data from CSV, JSON, and Notion into a unified schema?▼

To normalize data from CSV, JSON, and Notion into a unified schema, this Skill automatically detects delimiters, infers data types, and standardizes column names across heterogeneous sources for cross-source merging.

What is the best way to extract and merge Google Drive documents with CSV exports?▼

The best way to extract and merge Google Drive documents with CSV exports is using intelligent parsing that handles encoding detection and standardizes values across all sources into an analysis-ready dataset.

Can I consolidate customer feedback from a Notion database and text files for sentiment analysis?▼

Yes, you can consolidate customer feedback from a Notion database and text files by extracting and normalizing the heterogeneous data into a single unified schema ready for immediate sentiment analysis.

Does data normalization automatically infer data types from heterogeneous sources?▼

Yes, data normalization automatically infers data types from heterogeneous sources by intelligently parsing headers, detecting file encodings, and standardizing column values during the extraction process.

What happens if my CSV exports have inconsistent delimiters and headers during data extraction?▼

If your CSV exports have inconsistent delimiters and headers during data extraction, the intelligent parsing mechanism automatically detects delimiters and standardizes column names to resolve misalignment.

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