research

Crawl linked pages and organize findings into a structured README.

Updated Aug 23, 2026

Search Tags:#documentation #research #information gathering #web crawling #content aggregation #data synthesis

Ready to run

npx skills add https://github.com/ryanallen/product-studio --skill research-ryanallen

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research
Source: https://github.com/ryanallen/product-studio/tree/main/.claude/skills/research
Command: npx skills add https://github.com/ryanallen/product-studio --skill research-ryanallen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the process of gathering and organizing information from various user-provided inputs, making research more efficient and comprehensive.

Core Features & Use Cases

Multi-Source Ingestion: Accepts tickets, URLs, pasted text, images, and files as input.
Web Crawling: Follows links up to 5 levels deep to gather related content.
Structured Output: Organizes findings into a README with distinct sections for input, sources, grouped findings, and a link tree.
Use Case: A product manager needs to understand competitor features. They provide a competitor's website URL and a few key product names. The skill crawls the site, extracts relevant feature descriptions, and organizes them for review.

Quick Start

Use the research skill to gather information from the provided URL and write findings into the project README.

Frequently Asked Questions about research

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

FAQPage Schema

How do I gather and synthesize information from diverse sources like URLs and files?▼

To gather and synthesize information, provide tickets, URLs, text, images, or files as input. The skill crawls linked pages up to five levels deep, extracts relevant content, and organizes findings into a structured README file with grouped topics and a link tree.

Can I use web crawling to extract and organize content from a competitor's website?▼

Yes, web crawling extracts and organizes content from a competitor's website. By providing the site URL and key product names, the skill crawls up to five levels deep, extracts feature descriptions, and groups findings into a structured README for review.

What is the best way to aggregate data from multiple inputs into a structured README?▼

The best way to aggregate data into a structured README is using multi-source ingestion. The skill converts mixed inputs like pasted text and images into crawlable links or raw content, then outputs distinct sections for input, sources, grouped topics, and a link tree.

Does the research skill support prioritizing specific topics during content aggregation?▼

Yes, content aggregation supports prioritizing specific topics. You can focus the research by specifying target topics, which ensures the extracted content and grouped findings are organized according to your specified priorities in the final README.

What are the limitations of web crawling depth for information gathering?▼

The limitation for web crawling depth is a maximum of five levels deep. This boundary ensures the information gathering process extracts relevant content from linked pages without excessive crawling, structuring the output into a README with grouped topics.

How do I handle various input types like tickets and images for research?▼

To handle various input types like tickets and images for research, the skill automatically converts them into crawlable links or raw content. This allows the web crawling and data synthesis process to extract and organize findings seamlessly.