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data-research

Automate structured data research, extraction, and tracking from emails, web, and APIs.

Updated Aug 23, 2026
Search Tags:#structured data#data tracking#data deduplication#data research#email-to-structured-data
One-click install
npx skills add https://github.com/mscully4/franklin --skill data-research-mscully4
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-research
Source: https://github.com/mscully4/franklin/tree/main/.claude/skills/data-research
Command: npx skills add https://github.com/mscully4/franklin --skill data-research-mscully4

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of searching, extracting, and tracking structured data from various sources, reducing manual effort and ensuring data integrity.

Core Features & Use Cases

  • Structured Data Extraction: Extracts data from emails, web sources, and APIs.
  • Data Deduplication: Ensures data uniqueness and accuracy.
  • Tracker Updates: Updates and maintains canonical tracker pages.
  • Use Case: Ideal for investors tracking company performance or financial metrics through email updates and other sources.

Quick Start

Run the data-research skill with the recipe 'company-updates' to track your portfolio company's performance metrics.

Frequently Asked Questions about data-research

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

FAQPage Schema
How do I extract structured data from emails and track it automatically?▼

To extract structured data from emails, you need a system that parses incoming messages and maps them to specific fields. This Skill automates that email-to-structured-data conversion process while maintaining canonical tracker pages.

What is the best way to track company performance metrics from multiple sources?▼

The best way to track company performance metrics from multiple sources is to automate the extraction from emails, web, and APIs into a single tracker. This Skill uses YAML recipes to define and consolidate those specific tracking requirements.

How do I prevent duplicate entries when aggregating data from different APIs?▼

Preventing duplicate entries when aggregating data from different APIs requires a deduplication mechanism during ingestion. This Skill handles data deduplication automatically to ensure data uniqueness and accuracy across your tracker pages.

Do I need YAML recipes to use this data research and tracking Skill?▼

Yes, YAML recipes are required to use this data research and tracking Skill. You must define your specific data tracking requirements within a YAML recipe before the extraction and automation process can run.

Can I update canonical tracker pages automatically with new web data?▼

Yes, you can update canonical tracker pages automatically with new web data. This Skill automates the process of extracting web data and maintaining those canonical tracker pages to ensure your records remain current.

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