x-long-content-analyzer
PassAnalyze long tweets and X (Twitter) content. Use when user needs to read/summarize long tweets, extract key points, or analyze trends from Twitter/X content.
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Install globally (user-level):
npx skillhub install 19960705/clawd-skills/x-long-content-analyzerInstall in current project:
npx skillhub install 19960705/clawd-skills/x-long-content-analyzer --projectSuggested path: ~/.claude/skills/x-long-content-analyzer/
SKILL.md Content
---
name: x-long-content-analyzer
description: Analyze long tweets and X (Twitter) content. Use when user needs to read/summarize long tweets, extract key points, or analyze trends from Twitter/X content.
---
# X Long Content Analyzer
## Overview
This skill helps you analyze long-form Twitter/X tweets, extract key insights, identify trends, and generate summaries or responses. Use it when you share a tweet URL or want to analyze content from X.
## Quick Start
Determine what you need:
1. **Extract key points** - Summarize the main arguments and insights
2. **Analyze tone and style** - Understand the communication approach
3. **Identify trends and patterns** - Spot recurring themes
4. **Generate summaries** - Create concise overviews of long content
5. **Create responses** - Draft replies or follow-up content
## Core Functions
### 1. Content Summarization
For long tweets (>280 chars), break down into:
- **Main thesis**: Core argument or position
- **Key points**: Supporting arguments (3-5 main points)
- **Evidence**: Data, examples, or logical reasoning provided
- **Conclusion**: Final takeaway or call to action
### 2. Key Insight Extraction
Identify:
- **Trends mentioned**: Topics, movements, technologies
- **Controversies or debates**: Conflicting viewpoints
- **Data points**: Statistics, metrics, or research findings
- **Quotes or references**: Links to external content
### 3. Tone and Style Analysis
Assess:
- **Communication style**: Direct vs. diplomatic, aggressive vs. measured
- **Use of evidence**: Data-driven vs. anecdotal vs. hypothetical
- **Emotional appeal**: Logical vs. emotional, inspiring vs. neutral
- **Target audience**: General public vs. specific community
### 4. Response Generation
Create appropriate responses based on:
- **Agreement** - If you align with the author's position
- **Counter-argument** - If you disagree, provide evidence
- **Questions** - Asking for clarification or additional context
- **Summary** - Condensing long content for quick reading
## Resources
Load these references when working with analysis tasks:
- **Analysis Frameworks**: `references/analysis-frameworks.md` - Different ways to analyze content
- **Trend Patterns**: `references/trend-patterns.md` - Common patterns in tech and social media
- **Response Templates**: `references/response-templates.md` - Templates for different response types
## Usage Workflow
1. **Receive content** - User provides tweet URL, ID, or text content
2. **Extract or fetch** - Use web_fetch or bird CLI to get full content
3. **Analyze structure** - Identify main points, supporting arguments, and conclusions
4. **Generate output** - Create summary or response based on analysis
5. **Refine as needed** - Iterate based on user feedback
## Best Practices
### Summarization Guidelines
- **Be concise**: Capture essence in 3-5 bullet points
- **Preserve nuance**: Don't oversimplify complex arguments
- **Maintain objectivity**: Present different perspectives fairly
- **Highlight actionable takeaways**: What can the reader do with this information?
### Response Style
- **Match the author's tone** - If they're direct, be direct
- **Provide evidence** - Back up claims with data or logic
- **Stay constructive** - Even when disagreeing, remain respectful
- **Ask clarifying questions** - If something is unclear
## Tips for Long-Form Content
- **Break into sections**: Use headers or bullet points for readability
- **Use formatting**: Bold key terms, use quotes for emphasis
- **Include links**: If the content has references, preserve them
- **Note word count**: For very long threads, mention the length context