Multiple YouTubes cross analysis
Featured by
nene@YouMind.AI
Why we love this skill
Unify disparate YouTube content into a single, coherent narrative with this powerful skill. It intelligently cross-analyzes multiple videos on the same topic, generating a unified timeline, identifying conflicting viewpoints, and mapping terminology. Perfect for deep-diving into complex subjects and gaining a comprehensive understanding across various expert perspectives.
Instructions
Core Task
For 3–5 YouTube videos or podcasts on the same topic selected by the user. The goal: ignore source boundaries, build a unified timeline or logic tree, generate a Conflict Radar Report, and produce a Cross-Source Terminology Map.
Before executing, ask the user to select the YouTube videos/podcasts they want to analyze.
Step 1: Logical Alignment
Goal: Piece together the "fragments" from different creators into one coherent picture.
Actions:
De-duplicate & Reorganize: Ignore the original structure of videos A, B, and C. Group all content by theme—definitions, history, applications, etc.
Unified Framework: Arrange insights in a logical progression (e.g., What → Why → How) to create a comprehensive Master Guide.
Step 2: Conflict Radar
Goal: Sharpen critical thinking by identifying where experts disagree.
Actions:
Spot Contradictions: Scan for opinion clashes across sources (e.g., Creator A recommends a tool while Creator B warns against it).
Side-by-Side Comparison: Output a table listing the Point of Contention, Creator A's View, Creator B's View, and the reasoning behind each.
Content gerated attached to the "Logical Alignment" page.
Step 3: Terminology Mapping
Goal: Eliminate confusion caused by different terms for the same concept.
Actions:
Identify Aliases: Detect when different speakers use different names for the same idea (e.g., "loss function" vs. "cost function").
Generate a Mapping Table: Standardize terminology with a reference chart that notes each creator's "dialect."
Content gerated attached to the "Logical Alignment" page, right behind Conflict Radar
Make sure the output from three steps are wirtten on the same page.
description
Synthesize multiple YouTube episodes into a unified framework, automatically surface conflicting viewpoints, and build a more objective, well-rounded understanding.
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Multiple YouTubes cross analysis
Featured by
nene@YouMind.AI
Why we love this skill
Unify disparate YouTube content into a single, coherent narrative with this powerful skill. It intelligently cross-analyzes multiple videos on the same topic, generating a unified timeline, identifying conflicting viewpoints, and mapping terminology. Perfect for deep-diving into complex subjects and gaining a comprehensive understanding across various expert perspectives.
Instructions
Core Task
For 3–5 YouTube videos or podcasts on the same topic selected by the user. The goal: ignore source boundaries, build a unified timeline or logic tree, generate a Conflict Radar Report, and produce a Cross-Source Terminology Map.
Before executing, ask the user to select the YouTube videos/podcasts they want to analyze.
Step 1: Logical Alignment
Goal: Piece together the "fragments" from different creators into one coherent picture.
Actions:
De-duplicate & Reorganize: Ignore the original structure of videos A, B, and C. Group all content by theme—definitions, history, applications, etc.
Unified Framework: Arrange insights in a logical progression (e.g., What → Why → How) to create a comprehensive Master Guide.
Step 2: Conflict Radar
Goal: Sharpen critical thinking by identifying where experts disagree.
Actions:
Spot Contradictions: Scan for opinion clashes across sources (e.g., Creator A recommends a tool while Creator B warns against it).
Side-by-Side Comparison: Output a table listing the Point of Contention, Creator A's View, Creator B's View, and the reasoning behind each.
Content gerated attached to the "Logical Alignment" page.
Step 3: Terminology Mapping
Goal: Eliminate confusion caused by different terms for the same concept.
Actions:
Identify Aliases: Detect when different speakers use different names for the same idea (e.g., "loss function" vs. "cost function").
Generate a Mapping Table: Standardize terminology with a reference chart that notes each creator's "dialect."
Content gerated attached to the "Logical Alignment" page, right behind Conflict Radar
Make sure the output from three steps are wirtten on the same page.
description
Synthesize multiple YouTube episodes into a unified framework, automatically surface conflicting viewpoints, and build a more objective, well-rounded understanding.
Related Skills
View allIn-depth research and analysis of value investing
Enter a company name or stock, and the system will automatically connect to an exchange, perform a mandatory search before judgment, cross-reference data from two sources, and label the criteria and sources. It will conduct an in-depth analysis based on the seven-dimensional framework of value investing, provide three-scenario valuation and 2×2 quality/price decision-making, and generate an actionable "In-Depth Analysis of Value Investing" report.
Three-element analysis: Understanding the paper
Using the three-element decomposition method of identifying key elements, understanding the small loop, and mastering the large loop, this tool automatically or interactively dissects the argumentation framework of any paper. It includes 14 built-in AI Prompt templates, suitable for all academic readers.
Literature search on the method of peeling onions upside down
Enter a topic phrase, and it automatically breaks down the topic structure using the "onion peeling method" → expands synonyms → generates four-layer search queries (CNKI + WoS/Google Scholar), and provides an execution list and filtering strategy. Applicable to all disciplines, the search queries can be directly pasted and used. 🎯 What pain points does it solve? ❌ Directly entering a whole sentence into the search box → 0 results ❌ Searching for only one keyword → 5000 results with no idea where to start ❌ Not knowing how to break down a topic → No direction in search terms ✅ Enter "Middle-class educational anxiety and shadow education practices" → Output 30+ directly pasteable search queries + a thesaurus + a layered execution list 📐 Core method: The onion peeling method expands from the inside out, from narrow to wide, in three progressively deeper layers—the core layer precisely identifies 4 essential reading articles, the expansion layer finds 48 directly related studies, and the panoramic layer establishes a comprehensive understanding of the field's scope. 🔧 Output includes: • Breakdown of the three elements of topic selection (qualifiers + research unit + research dimension) • 5-8 related concepts for each element + Chinese-English comparison + superordinate/subordinate concepts • First layer: 8 sets of three-element combination search formulas (title → topic, tight → loose) • Second layer: 3 types of two-element pairings (marking core/background uses) • Third layer: Single-element panoramic search formula • Fourth layer: Superordinate concept expansion strategy • 📋 Six-step execution checklist + screening criteria for each layer (highly cited + cutting-edge) 👥 Who is it suitable for? Academic novices, graduate students, young scholars—anyone who needs to systematically conduct literature searches rather than searching keywords based on intuition.
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