last30days: The AI Skill That Searches People, Not Editors
TL;DR
- What it solves: You have a meeting in the morning. You Google the person and get a LinkedIn page from 2023. What they actually said and shipped this month is scattered across Reddit, X, YouTube, and GitHub, and Google indexed none of the good parts.
- Why it matters: The community figures things out months before the training data and the blog posts catch up. Miss the last 30 days and you walk into the room already behind.
- Best for: Anyone who preps. Before a sales call, a job interview, a trip, or shipping a feature. And developers who need current prompts, not last year’s.
- Main differentiator: It ranks by what real people upvoted, liked, watched, and bet money on. Social relevancy, not SEO relevancy.
- Best use case:
/last30days Peter Steinbergerand in three minutes you know he joined OpenAI’s Codex team, shipped 23 PRs at an 85% merge rate, and that r/ClaudeCode burned 569 upvotes arguing about him.
You have a meeting tomorrow. You Google them. You get their LinkedIn from 2023.
What they actually did this month lives in twelve other places. A Reddit thread arguing about them. A 45-minute podcast nobody transcribed. Twenty-three commits on GitHub. A Polymarket bet on whether they will tweet again. None of it is on the first page of Google, because Google was never invited into those rooms.
What last30days Actually Is
It is one thing you install into your AI agent: a SKILL.md instruction file plus a Python engine. Type /last30days <topic> and it fans out across a dozen platforms at once, scores every result by engagement, and an AI judge folds it all into a single brief.
Nothing to configure on day one. Reddit, Hacker News, Polymarket, and GitHub work the moment you install it. Run it once and a 30-second wizard unlocks X, YouTube, and TikTok when you want them.
Google Aggregates Editors. This Searches People.
Picture two ways to learn what is happening. One is a newsstand, where editors decided last week what was worth printing. The other is the stadium, where you can hear what the crowd is actually chanting, see who they are betting on, and watch which section is losing its mind right now.
That is the whole bet. A Reddit thread with 1,500 upvotes is a stronger signal than a blog post nobody read. A TikTok with 3.6M views tells you more about the culture than a press release. Polymarket odds backed by real money are harder to argue with than a pundit. The synthesis ranks by what people actually engaged with, not by who won at SEO.
The One Command
The friendliest way to get it is one line. Everything after that is plain English.
# Claude Code (auto-updates via the marketplace)
/plugin marketplace add mvanhorn/last30days-skill
/plugin install last30days
# Codex, Cursor, Copilot, Gemini CLI, and 50+ other hosts
npx skills add mvanhorn/last30days-skill -g
# Then just ask
/last30days Peter SteinbergerThe output has a fixed shape, on purpose. A version badge on the first line, then “What I learned”, then short bold-lead paragraphs grounded in real posts, then a numbered list of key patterns, and a “Best Takes” section for the funniest lines the crowd produced. No trailing wall of links.
Why No Single AI Can Do This
Every platform is a walled garden with its own API and its own login. Google search never touches Reddit comments or X posts. ChatGPT has a deal with Reddit but cannot search X or TikTok. Gemini has YouTube but not Reddit. Claude has none of them natively. But you bring your own keys and browser sessions, and suddenly one agent searches all of them at once and scores them against each other.
That is the unlock. Not one better search engine. A dozen disconnected platforms, bridged by an agent that can finally read all of them in the same breath.
Scored, Merged, Ranked
Each source tells you a different kind of truth, and the engine knows the difference.
| Source | What it tells you |
|---|---|
| The unfiltered take. Top comments with upvote counts, free | |
| X | The hot take and the expert thread. First to argue |
| YouTube | The 45-minute deep dive, searched for the 5 quotes |
| Hacker News | The developer consensus. Where technical people fight |
| Polymarket | Not opinions. Odds, backed by real money |
| GitHub | For people: PR velocity, top repos, release notes |
The pipeline is a short relay, and the order matters:
- Resolve who actually matters for the topic, before searching.
- Search every source in parallel, scored by engagement.
- Merge the same story when it shows up on Reddit, X, and YouTube.
- Synthesize one brief, cited by source.
- End with the cleverest lines the crowd produced.
What v3 Changed
The clever part is the search before the search. Type “OpenClaw” and the engine first resolves the founder’s X handle, the right subreddits, and the YouTube channels that matter, then searches those instead of guessing at keywords. It understands the topic before it touches an API.
There is also a second judge that scores for humor and virality, not just relevance, so every brief ends with the one-liners worth repeating. And the engine grew flags for the way people actually work: --emit=html for a shareable brief, --competitors to auto-discover rivals, --github-user for person-mode, and “eli5 on” when you want it in plain language.
Where It Fits, Where It Doesn’t
Use it when recency is the whole point. Skip it when it is not.
The Rough Edges
The free tier is real, but the best sources cost something. X wants you logged into a browser. TikTok, Instagram, and Threads ride on a ScrapeCreators key: 100 free credits, then pay as you go. Perplexity needs an OpenRouter key. The opt-in design protects you from surprise bills, but you should know which platforms cost money before you reach for them.
⚠️ Warning: “Paid source” is per-call. A wide run that pulls TikTok, Instagram, and YouTube comments can spend ScrapeCreators credits faster than you expect. Start narrow.
There is a deeper limit, and it is not a bug. Engagement is not truth. A viral take is still just a popular one, and the 30-day window forgets everything older on purpose. The tool caps each author at three items so no single loud voice owns your brief, but it cannot tell you that the loudest room is also the right one. That part is still your job.
💡 Tip: Start with the free four, then add one key the first time a run leaves an obvious gap. And read the brief like a smart, biased friend, not a verdict.
Final Thoughts
The repo is four and a half months old and already past 29,000 stars, which tells you how many people were quietly doing this by hand: opening Reddit in one tab, X in another, a YouTube transcript in a third, before every meeting that mattered.
It will not tell you the truth. It tells you what the crowd is saying, loudly, this month, with the receipts attached. Walking into the room knowing that beats walking in with a LinkedIn page from 2023.
mvanhorn/last30days-skill · MIT · 29k
Hoang Yell
A software developer and technical storyteller. I spend my time exploring the most interesting open-source repositories on GitHub and presenting them as accessible stories for everyone.
