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reddit-thread-analyzerReddit 线程分析器

Agent Skill

reddit-thread-analyzer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

6,536

周安装

267

GitHub Stars

103

下载量

2,115
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:reddit-thread-analyzer(Reddit 线程分析器)
来源仓库:https://github.com/onewave-ai/claude-skills
仓库路径:skills/reddit-thread-analyzer
安装命令:
npx skills add https://github.com/onewave-ai/claude-skills --skill reddit-thread-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/onewave-ai/claude-skills --skill reddit-thread-analyzer

简介

用于分析和处理 Reddit 线程内容。reddit-thread-analyzer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适合提取帖子信息、识别讨论主题和情感倾向。
  • 通过 npx 命令从 GitHub 仓库安装使用。
  • 需确认权限范围和维护状态,注意可能触发联网操作。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

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:

  1. Fetch r/apple or r/iPhone thread
  2. Analyze 300+ comments
  3. Determine sentiment: Mixed (55% positive, 45% negative)
  4. Extract top pros: Camera improvements (+450), Performance (+380)
  5. Extract top cons: High price (+420), Incremental updates (+390)
  6. Note consensus: Good phone, but expensive for what you get
  7. Identify controversy: Whether it's worth upgrading from iPhone 14
  8. Surface expert opinions from tech reviewers
  9. Deliver structured report with quotes and scores

Remember: Focus on substance over noise. Prioritize well-reasoned arguments over emotional reactions.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.9%
按下载量换算632

Codex

24.24%
按下载量换算513

Antigravity

17.79%
按下载量换算376

windsurf

12.72%
按下载量换算269

OpenCode

7.77%
按下载量换算164

Cursor

3.18%
按下载量换算67

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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