The agent that searches everything Google can't: /last30days bridges the walled gardens

An AI agent skill called /last30days now searches Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the open web in a single pass, then synthesizes a ranked summary. The GitHub repository describes it as “an AI agent-led search engine scored by upvotes, likes, and real money — not editors.”

The claim is direct: “Google aggregates editors. /last30days searches people.”

That framing is the story. The skill does not try to build a better search engine. It builds a bridge across walled gardens. Google cannot search Reddit comments or X posts natively. ChatGPT has a deal with Reddit but not X or TikTok. Gemini has YouTube but not Reddit. Claude has none of them. Each platform holds its own API, its own authentication, its own token economics. /last30days lets the user bring their own keys and browser sessions, then the agent queries all of them simultaneously, scores results by engagement metrics (upvotes, likes, view counts, Polymarket odds backed by real money), and an AI judge synthesizes the output into a single brief.

The concrete example in the README is Peter Steinberger, the creator of OpenClaw. A Google search returns a LinkedIn profile from 2023. /last30days returns that he joined OpenAI’s Codex team, is fighting Anthropic’s ban on third-party agents, shipped 23 PRs at an 85% merge rate, is building “LobsterOS” for cross-device agent control, and a Reddit thread on r/ClaudeCode hit 569 upvotes debating whether he is a hero or “insufferable.” None of that content was on Google.

This is not a marginal improvement. It is a different search paradigm. Traditional search indexes pages and ranks them by link authority and keyword relevance. /last30days indexes social signals and ranks them by human engagement. A Reddit thread with 1,500 upvotes is a stronger signal than a blog post nobody read. A TikTok with 3.6 million views tells you more about cultural relevance than a press release. Polymarket odds backed by $66,000 in volume are harder to argue with than a pundit’s guess.

The skill runs as a plugin for Claude Code, Codex, Cursor, Copilot, Gemini CLI, or any of the 50-plus Agent Skills hosts. Installation is a single command: npx skills add mvanhorn/last30days-skill -g. Zero configuration gets Reddit, Hacker News, Polymarket, and GitHub working immediately. A setup wizard unlocks X, YouTube, TikTok, and others in roughly 30 seconds.

The v3 pipeline, documented in the repository, adds several structural improvements. The engine now resolves topics before searching. Type “OpenClaw” and a Python pre-research brain, built by a contributor named @j-sperling, resolves the handle @steipete (Peter Steinberger), the subreddits r/openclaw and r/ClaudeCode, and the relevant YouTube channels and TikTok hashtags. The old engine searched keywords. The new engine understands the topic first, then searches the right people and communities.

The skill also adds a second judge that scores results for humor, wit, and virality alongside relevance. Every brief now ends with a “Best Takes” section: the cleverest one-liners, the most viral quotes, the reactions that make you want to share the research. Cross-source cluster merging detects when the same story appears on Reddit, X, and YouTube and merges them into one item instead of showing three separate results. Entity-based overlap detection catches matches even when the titles use different words.

A single-pass comparison mode runs entity-aware subqueries for both sides simultaneously. /last30days CLI vs MCP used to run three serial passes taking 12-plus minutes. v3 runs one pass in roughly three minutes. An auto-discovered competitor comparison mode lets the hosting reasoning model discover the top two peers via web search, then fans out three full pipelines in parallel and merges them into a multi-way comparison.

GitHub person-mode switches from keyword search to author-scoped queries when the topic is a person. Instead of “who mentioned this name in an issue body,” it answers: what are they shipping and where is it landing? For Peter Steinberger with the --github-user=steipete flag, it shows 22 PRs merged across three repos at an 85% merge rate, own projects with README summaries and star counts, and release notes for what shipped that month.

The implications for AI research and development are structural. The training data for frontier models is always months behind what the community has already figured out. The README says the creator built it to keep up in AI: “Everything changes every day and the Reddit and X nerds are always on top of it first. I needed better prompts, and the training data was always months behind what the community had already figured out.” That gap between training data and community knowledge is the core problem /last30days solves. It is not a research tool. It is a real-time community intelligence feed.

The skill also reveals something about the economics of AI agents. Each platform is a walled garden with its own API, its own tokens, its own authentication. No single AI company has access to all of them. Google cannot search Reddit comments or X posts. ChatGPT has a deal with Reddit but not X or TikTok. Gemini has YouTube but not Reddit. Claude has none of them natively. The agent that bridges all of them is not a product from a frontier lab. It is an open-source skill that asks the user to bring their own keys.

That is the unlock. Not one better search engine. A dozen disconnected platforms, bridged by an agent that the user controls.

The open question is whether the walled gardens will close. If Reddit, X, and YouTube see agents scraping their content at scale and synthesizing it outside their own interfaces, they may tighten API access or change their terms of service. The skill already relies on users bringing their own keys, which distributes the liability but does not eliminate it. The platforms could also build their own agent search products. X already has Grok. Reddit has a deal with ChatGPT. YouTube has Gemini.

But for now, /last30days works. It runs on a single command. It searches what Google cannot. And it scores by what real people actually engage with, not by what a search engine algorithm decides is authoritative. That is a different kind of search. And for anyone trying to keep up with AI, it may be the only kind that works.