content-analysis

Extract entities, claims, sentiment, framing, and narrative from text.

Updated Apr 1, 2026

Search Tags:#narrative #claims-analysis #content-analysis #sentiment #framing #text-analysis #entity-extraction

Ready to run

npx skills add https://github.com/hpsgd/turtlestack --skill content-analysis-hpsgd

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: content-analysis
Source: https://github.com/hpsgd/turtlestack/tree/main/plugins/research/analyst/skills/content-analysis
Command: npx skills add https://github.com/hpsgd/turtlestack --skill content-analysis-hpsgd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This analysis tool provides a structured approach to understand text by extracting entities, key claims, sentiment, framing, and narrative elements, enabling deeper insights beyond surface content.

Core Features & Use Cases

Entity extraction: identify People, Organisations, Locations, Dates, Products, and Financial figures.
Claim and sentiment analysis: surface primary and supporting claims, sentiment, and framing.
Narrative identification: detect dominant storylines and perspective.
Use cases: content review, journalism, policy analysis, and research tasks requiring deep textual understanding.

Quick Start

Paste content or provide a URL to analyze, and I will return a structured content analysis.

Frequently Asked Questions about content-analysis

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

FAQPage Schema

How do I perform structured text analysis on an article to extract entities and framing?▼

Structured text analysis extracts entities, key claims, sentiment, framing, and narrative elements from pasted content or a URL. It returns a multi-part analysis detailing not just what is said but how it is said, applicable to content review, journalism, policy analysis, and research tasks.

What is narrative framing analysis and when do I need it for content review?▼

Narrative framing analysis detects dominant storylines, perspective, sentiment, and how claims are presented within text. You need it for content review, journalism, and policy analysis where understanding how information is framed matters beyond the surface content.

Can I analyze text from a URL or do I need to paste the content directly?▼

You can analyze text from either a URL or by pasting content directly. The tool requires one of these inputs to perform structured entity extraction, claim analysis, sentiment evaluation, and narrative identification.

What types of entities can entity extraction identify during text analysis?▼

Entity extraction identifies People, Organisations, Locations, Dates, Products, and Financial figures within the text. This structured extraction supports deeper insights for research, journalism, and policy analysis tasks.

Does this content analysis approach work for policy analysis and research tasks?▼

Yes, content analysis applies directly to policy analysis and research tasks. It surfaces primary and supporting claims, detects sentiment and framing, and identifies narrative elements to provide deep textual understanding.

What is the best way to extract key claims and sentiment from a document?▼

The best way to extract claims and sentiment is using structured text analysis, which surfaces primary and supporting claims alongside sentiment and framing. This provides a multi-part breakdown of the document's source structure and narrative elements.