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name: last30days description: > AI agent-led search engine that researches any topic across Reddit, X (Twitter), YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, and more — scored by real engagement signals (upvotes, likes, comments) rather than SEO. Produces rich HTML briefs with Best Takes, cross-source cluster merging, ELI5 mode, comparison mode, hiring signals, and competitor auto-discovery. Use when the user wants to research what people are saying about a topic, product, person, or trend in the last 30 days. Trigger keywords: /last30days, research, what are people saying, trending, sentiment, compare, ELI5, hiring signals, best takes, 调研, 最近30天, 大家都在说什么, 海外调研, AI新概念学习, 海外资讯, 社交媒体调研, 热门话题, 深度搜索, Reddit搜索, X搜索, 跨平台调研. metadata: category: thinking source: https://github.com/mvanhorn/last30days-skill references: - https://mp.weixin.qq.com/s/VDlBdkspV0SQNFJYLxOogQ author: original: mvanhorn chinese_intro: 卡兹克

last30days — AI-Powered Topic Research

An AI agent-led search engine that researches any topic across 15+ platforms scored by real engagement signals, not SEO or editorial curation.

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Installation

# Claude Code (recommended — auto-updates via marketplace)
claude plugin marketplace add mvanhorn/last30days-skill
claude plugin install last30days@last30days-skill

# Other agents (Codex, Cursor, Copilot, Gemini CLI, etc.)
npx skills add mvanhorn/last30days-skill -g

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Usage

/last30days <topic> [--mode <mode>] [--save]

Modes: research (default), compare, hiring, agent, eli5

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What it searches

Source	What it captures
Reddit	Thread scores, comment counts, subreddit communities
X (Twitter)	Tweet engagement, verified signals
YouTube	Video metadata, view counts
TikTok	Trending short-form content
Instagram	Visual trend signals
Hacker News	Tech community discussion scores
Polymarket	Real-money prediction market odds
GitHub	Repo stars, issue activity, person/org mode
Threads, Pinterest, Bluesky	Emerging platform signals
Perplexity	AI-powered web research
General Web	Brave/Exa/Serper search backends

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Key features

• Real engagement signals — upvotes, likes, comment counts, Polymarket odds
• Best Takes — extracts the most insightful comments/threads
• Cross-source cluster merging — deduplicates the same story across platforms
• ELI5 mode — simple explanations for complex topics
• Comparison mode — side-by-side analysis (e.g., "Cursor vs Copilot")
• Hiring signals — candidate/business evaluation patterns
• GitHub person-mode — research a developer's activity profile
• Shareable HTML briefs — self-contained reports with embedded media

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Configuration

Config file at ~/.config/last30days/.env or .claude/last30days.env:

REDDIT_CLIENT_ID=...
REDDIT_CLIENT_SECRET=...
X_BEARER_TOKEN=...
SCRAPECREATORS_API_KEY=...
BLUESKY_APP_PASSWORD=...
PERPLEXITY_API_KEY=...
BRAVE_API_KEY=...

Output saved to ~/Documents/Last30Days/ (configurable via LAST30DAYS_MEMORY_DIR).

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Architecture

skills/last30days/
├── SKILL.md              # Canonical skill definition (10 LAWs + step-by-step)
└── scripts/
    ├── last30days.py     # Main engine
    └── lib/              # Source modules, search backends, scoring

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中文介绍

以下内容整理自卡兹克的介绍文章：《开源项目简介：last30days》

这是什么？

给 last30days 一个话题，它让 AI agent 帮你扒一遍最近 30 天国外各大社交媒体上的真实讨论，然后综合成一份带引用的报告。

开源地址：https://github.com/mvanhorn/last30days-skill

和普通搜索的核心差异

第一，深度爬取，不只是看帖子标题。

Reddit 上一个帖子，它把评论带点赞数一起扒下来。X 上的推文，高赞回复也会纳入进去。就像你看小红书不会只看正文肯定要翻评论区一样，这个 Skill 把类似的考虑了进去，而且跨十几个平台一起翻。优质信息经常就埋在评论里，有时候评论比正文还值钱。

第二，按真实热度排序，不按 SEO。

Reddit 几千 upvote 的讨论，权重高于一篇没人看的博客。一个 3.6M 播放的 TikTok，权重高于一篇新闻稿。看到的排名是真人投出来的，不是哪篇博客做了 SEO 排上来的。

覆盖源

Reddit、X、YouTube、TikTok、Hacker News、GitHub、Polymarket 等十几个国外平台。

免费 vs 付费

• 零配置免费可用：Reddit、Hacker News、Polymarket、GitHub
• 简单配置后可用：X（登录浏览器账号或用 API key）、YouTube（装 yt-dlp）
• 免费源对日常学习新概念来说已经够用

适用场景

学习 AI 新概念新知识特别好用——国内很多信息是对海外资讯的搬运和二次咀嚼，直接用这个 Skill 从源头获取，信息更一手、更及时。

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MIT License.