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Reddit Thread Analyzer
Extract deep insights from Reddit discussions including sentiment, key arguments, and community consensus.
When a user provides a Reddit thread URL or asks about Reddit opinions, analyze the discussion comprehensively to surface meaningful patterns and insights.
Instructions
1. Fetch and Parse Thread Data
Use WebFetch to load the Reddit thread and extract:
- Post title, body, author, score, and timestamp
- All comments (not just top-level)
- Comment scores, awards, and timestamps
- Note verified contributors or expert flair
2. Analyze Overall Sentiment
Determine the dominant sentiment and emotional tone:
- Overall sentiment : Positive, negative, neutral, or mixed
- Sentiment distribution : Approximate percentages
- Emotional tone : Excited, frustrated, skeptical, supportive, angry, enthusiastic
- Shift over time : Note if sentiment changes throughout discussion
3. Extract Key Arguments
Identify the most impactful points:
Top Arguments in Favor (3-5 points):
- Quote the argument
- Note comment score
- Identify supporting evidence or reasoning
Top Arguments Against (3-5 points):
- Quote the argument
- Note comment score
- Identify counter-points and rebuttals
Expert or Verified Opinions :
- Highlight comments from verified experts
- Note OP responses and clarifications
4. Find Consensus Points
Determine what the community agrees on:
- Points with broad agreement (high scores, no controversy)
- Emerging patterns across multiple comments
- Common ground between opposing viewpoints
5. Identify Controversial Topics
Flag heavily debated points:
- Topics with mixed upvotes/downvotes
- Arguments that sparked long comment chains
- Divisive issues where community is split
6. Provide Structured Analysis
Format your analysis clearly:
# Reddit Analysis: [Thread Title]
## Executive Summary
[2-3 sentence overview of the discussion and main takeaway]
## Overall Sentiment
- **Dominant Sentiment**: Positive/Negative/Neutral/Mixed (X%)
- **Emotional Tone**: [excited/frustrated/skeptical/etc.]
- **Community Alignment**: High/Medium/Low
## Top Arguments
### In Favor
1. **[Main point]** (+XXX score)
> "[Direct quote from comment]"
- [Brief explanation of reasoning]
2. **[Main point]** (+XXX score)
> "[Direct quote]"
### Against
1. **[Main point]** (+XXX score)
> "[Direct quote]"
## Community Consensus
- ✅ [Point most people agree on]
- ✅ [Another consensus point]
## Controversial Topics
- ⚠️ [Divisive issue] - Community split roughly 50/50
- ⚠️ [Another debate point]
## Notable Insights
- **Expert Opinion**: [Quote from verified expert] (+XXX)
- **Surprising Take**: [Unexpected perspective that gained traction]
- **Most Helpful**: [Most practical or actionable advice]
## Key Quotes
> "[Memorable quote]" - u/username (+XXX score)
> "[Another impactful quote]" - u/username (+XXX score)
## Discussion Quality
- Civility: High/Medium/Low
- Depth: Superficial/Moderate/Deep
- Evidence-based: Yes/No/Mixed
Best Practices
- Focus on highly upvoted comments for consensus
- Include exact scores to show community agreement level
- Quote directly rather than paraphrasing
- Preserve nuance - avoid oversimplifying complex debates
- Note OP responses - original poster often adds important context
- Distinguish facts from opinions clearly
- Highlight constructive vs. unproductive discussions
- Consider recency - early comments may be less informed than later ones
Example Analysis
User : "What does Reddit think about the new iPhone?"
Your analysis :
- Fetch r/apple or r/iPhone thread
- Analyze 300+ comments
- Determine sentiment: Mixed (55% positive, 45% negative)
- Extract top pros: Camera improvements (+450), Performance (+380)
- Extract top cons: High price (+420), Incremental updates (+390)
- Note consensus: Good phone, but expensive for what you get
- Identify controversy: Whether it's worth upgrading from iPhone 14
- Surface expert opinions from tech reviewers
- Deliver structured report with quotes and scores
Remember : Focus on substance over noise. Prioritize well-reasoned arguments over emotional reactions.
Weekly Installs
184
Repository
onewave-ai/claude-skills
GitHub Stars
67
First Seen
Jan 24, 2026
Security Audits
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