What Is /last30days? The AI Agent Research Tool That Searches People, Not Editors
Purpose
When I need to research a topic across social media, I used to tab-hop between Reddit, X, YouTube, Hacker News, and half a dozen other sites. Each platform is a walled garden — Reddit has content Google can’t index well, X is behind login walls, TikTok is entirely opaque to traditional search. There’s no single tool that searches them all at once.
/last30days solves this. It’s an AI agent skill (a slash command) that researches any topic across 10+ platforms — Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the web — then scores and synthesizes results by what real people actually engage with, not what SEO algorithms rank highest.
The Problem
Traditional search engines like Google rank by backlinks, SEO signals, and editorial curation. That works well for evergreen content — documentation, reference articles, established knowledge. But for what’s happening right now:
- Google surfaces blog posts nobody read because they have good SEO
- ChatGPT has a licensing deal with Reddit but can’t access X or TikTok
- Each social platform is a walled garden with its own search
The result: researching a current topic means opening 6 browser tabs and manually cross-referencing.
The Solution
/last30days bridges these disconnected platforms through a single slash command:
/last30days <topic>That’s it. One command searches all platforms in parallel, scores results by real engagement, and an AI judge synthesizes everything into one research brief.
Here’s the architecture:
User types: /last30days <topic> │ ▼┌─────────────────┐│ Host AI Model │ reads SKILL.md contract│ (Claude/Codex) │ knows which flags to pass└────────┬────────┘ │ ▼┌─────────────────┐│ Python Engine │ scripts/last30days.py│ (last30days.py) │ fans out to 10+ sources└────────┬────────┘ │ ┌────┼────┬────┬────┬────┬────┐ ▼ ▼ ▼ ▼ ▼ ▼ ▼ Reddit X YT HN GH Poly Web │ │ │ │ │ │ │ └────┴────┴────┴───┴────┴────┘ │ ▼┌─────────────────┐│ Fusion + Judge │ scores by engagement│ + Synthesis │ produces research brief└─────────────────┘The key difference from traditional search: each result is scored by real engagement signals — Reddit upvotes, X likes, YouTube views, Polymarket odds backed by real money. The synthesis ranks by social relevancy, not SEO relevancy.
Why Engagement Over SEO
A Reddit thread with 1,500 upvotes tells you more about what’s actually happening than a blog post nobody read. A Polymarket contract with $66K in volume is harder to argue with than a pundit’s guess. TikTok views reveal cultural relevance that a press release hides.
| Platform | Scoring Signal | Why It Matters |
|---|---|---|
| Upvote counts | Community consensus | |
| X | Likes, retweets | Real-time signal |
| YouTube | Views, likes | Watch-time attention |
| Polymarket | Odds + volume | Money-backed belief |
| Hacker News | Points, comments | Tech community signal |
Summary
In this post, I explained what /last30days is and how it differs from traditional search. The key point is that /last30days is not a search engine — it’s an agent bridge across the walled gardens of social media. Run /last30days <topic> from any supported AI coding tool, and get synthesized research scored by what real people actually engage with.
Final Words + More Resources
My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me
Here are also the most important links from this article along with some further resources that will help you in this scope:
Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!
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