last30days-skill is a Claude Code agent skill that has crossed 31,400 GitHub stars by replacing the editorial assumptions of conventional search with a simple one: ask people, not editors. Given a topic — a person, a company, a product, or a head-to-head comparison — the skill fans out across Reddit, X, YouTube transcripts, Hacker News, Polymarket prediction markets, TikTok, Instagram, Threads, Bluesky, GitHub, and editorial web search in parallel, then synthesizes the results into a single brief ranked by actual engagement signal: upvotes, likes, video views, prediction market dollar weight, and merged-PR rate. The slogan in the README — "Google aggregates editors. /last30days searches people." — is the entire product thesis in one line. ## What the Skill Is For The skill targets the specific knowledge gap that has opened up since LLM training cutoffs and editorial search both stopped tracking the live web at engagement-level resolution. Asking a stock LLM "what happened with [topic] in the last 30 days" returns either a refusal or a confidently wrong summary. Asking Google returns the editorial coverage that already existed before the topic mattered. Running /last30days on the same topic returns the upvoted Reddit threads, the highest-engagement X posts, the YouTube videos with the most views, the GitHub repos with the most recent PRs, and the Polymarket markets where actual money is being staked — and clusters duplicate stories together so each finding appears once with the strongest source attached. ## Sources and Multi-Query Expansion The ten data sources are not queried with a single literal string. The skill performs entity resolution first — distinguishing a person from a company with the same name, finding the right subreddit, mapping a product to its GitHub org, identifying the canonical X handle and hashtag — and then expands each topic into a multi-query plan tuned for each source. Reddit gets a different query than YouTube, Polymarket gets a different query than Hacker News, and the merge step normalizes engagement metrics across sources so a 50,000-view TikTok and a 200-upvote HN thread can be ranked against each other on a single scale. The README documents 1,012 passing tests, which is unusual for an agent skill repository and reflects the entity-resolution complexity that makes the rest of the pipeline work. ## The Output: Shareable HTML Briefs The brief that gets generated is a single self-contained HTML file with dark mode, offline functionality, inline citations to every cited source, a "Best Takes" section that surfaces the wittiest viral reactions and quotes, and an optional ELI5 mode for non-technical readers. Because the file is self-contained, briefs can be shared with non-Claude-users by email or chat without any cloud dependency on the part of the recipient. This is the differentiator over running raw web searches yourself: the synthesis, the engagement-weighted ranking, the duplicate cluster, and the shareable artifact are all built in. ## Installation and Distribution The skill installs into Claude Code via the marketplace command `/plugin marketplace add mvanhorn/last30days-skill`, or via the Agent Skills CLI with `npx skills add mvanhorn/last30days-skill -g`, or by uploading the released `.skill` file through Settings > Capabilities > Skills on the web client. Initial setup for Reddit, Hacker News, Polymarket, and GitHub requires zero credentials — these sources are queried through public endpoints. X, YouTube, TikTok, Instagram, Threads, and Bluesky require either credentials or social-platform access tokens depending on the depth of search needed. ## Limitations The skill is one of the largest and most visible examples of the Claude Code agent-skill marketplace pattern, and that visibility is also the constraint: it is opinionated about being a Claude Code skill and is not trivially portable to other agent runtimes. The dependency on platform-specific access for X, YouTube, and the meta-controlled platforms means coverage there will move with whatever access regime those platforms enforce next. Engagement-ranked output is great at surfacing what people actually paid attention to and bad at surfacing what is true — viral wrongness ranks higher than quiet correctness, and the brief format does not currently flag this asymmetry. Finally, the "last 30 days" framing means the skill is not the right tool for historical or evergreen research, which is a feature, not a bug, but worth stating. Within those bounds, /last30days is the most polished demonstration to date of what a single well-built Claude Code skill can do in 2026, and a useful reference for any team building agent skills of their own.