reddit-thread-analyzer by onewave-ai/claude-skills
npx skills add https://github.com/onewave-ai/claude-skills --skill reddit-thread-analyzer从 Reddit 讨论中提取深度见解,包括情绪、关键论点以及社区共识。
当用户提供 Reddit 帖子 URL 或询问关于 Reddit 上的观点时,全面分析讨论以揭示有意义的模式和见解。
使用 WebFetch 加载 Reddit 帖子并提取:
确定主导情绪和情感基调:
识别最有影响力的观点:
支持方的顶级论点(3-5 点):
反对方的顶级论点(3-5 点):
专家或已验证的观点:
确定社区达成一致的内容:
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标记激烈辩论的要点:
清晰地格式化你的分析:
# Reddit 分析:[帖子标题]
## 执行摘要
[2-3 句话概述讨论内容和主要结论]
## 整体情绪
- **主导情绪**:积极/消极/中性/混合 (X%)
- **情感基调**:[兴奋/沮丧/怀疑等]
- **社区一致性**:高/中/低
## 顶级论点
### 支持方
1. **[主要观点]** (+XXX 评分)
> "[评论中的直接引用]"
- [推理的简要说明]
2. **[主要观点]** (+XXX 评分)
> "[直接引用]"
### 反对方
1. **[主要观点]** (+XXX 评分)
> "[直接引用]"
## 社区共识
- ✅ [大多数人同意的观点]
- ✅ [另一个共识点]
## 争议性话题
- ⚠️ [分歧性问题] - 社区大致 50/50 分裂
- ⚠️ [另一个辩论点]
## 值得注意的见解
- **专家观点**:[来自已验证专家的引用] (+XXX)
- **出人意料的观点**:[获得关注的非预期视角]
- **最有帮助的**:[最实用或可操作的建议]
## 关键引用
> "[令人印象深刻的引用]" - u/用户名 (+XXX 评分)
> "[另一个有影响力的引用]" - u/用户名 (+XXX 评分)
## 讨论质量
- 文明程度:高/中/低
- 深度:浅显/中等/深入
- 基于证据:是/否/混合
用户:"Reddit 对新 iPhone 有什么看法?"
你的分析:
记住:关注实质内容而非噪音。优先考虑经过深思熟虑的论点而非情绪化的反应。
每周安装量
184
代码仓库
GitHub 星标数
67
首次出现
2026年1月24日
安全审计
安装于
gemini-cli159
opencode159
codex155
cursor150
github-copilot142
kimi-cli127
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.
Use WebFetch to load the Reddit thread and extract:
Determine the dominant sentiment and emotional tone:
Identify the most impactful points:
Top Arguments in Favor (3-5 points):
Top Arguments Against (3-5 points):
Expert or Verified Opinions :
Determine what the community agrees on:
Flag heavily debated points:
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
User : "What does Reddit think about the new iPhone?"
Your analysis :
Remember : Focus on substance over noise. Prioritize well-reasoned arguments over emotional reactions.
Weekly Installs
184
Repository
GitHub Stars
67
First Seen
Jan 24, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykWarn
Installed on
gemini-cli159
opencode159
codex155
cursor150
github-copilot142
kimi-cli127
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