last30days — agent skill that searches social platforms, scores by engagement, and synthesizes grounded briefs | mvanhorn/last30days-skill | DocsDigest
An AI agent-led search engine scored by upvotes, likes, and real money - not editors.
This README tracks the current v3 pipeline. The runtime skill spec lives in skills/last30days/SKILL.md, which is the source of truth for the latest command and setup behavior.
Claude Code (recommended — auto-updates via marketplace):
Codex, Cursor, Copilot, Gemini CLI, or any of 50+ Agent Skills hosts:
npx skills add mvanhorn/last30days-skill -g
(-g installs globally for your user, available across all projects. Drop it to scope per-project.)
More install options (claude.ai web, OpenClaw, manual) in the Install section below.
Zero config. Reddit, HN, Polymarket, and GitHub work immediately. Run it once and the setup wizard unlocks X, YouTube, TikTok, and more in 30 seconds.
Reddit upvotes. X likes. YouTube transcripts. TikTok engagement. Polymarket odds backed by real money and insider information. That's millions of people voting with their attention and their wallets every day. /last30days searches all of it in parallel, scores it by what real people actually engage with, and an AI agent judge synthesizes it into one brief.
/last30days is a Python AI agent skill that researches any topic across Reddit, X, YouTube, Hacker News, Polymarket, GitHub and many more sources in parallel, scores results by real-world engagement (upvotes, likes, views, and money), and synthesizes a grounded summary. The README is the source of truth for the v3 pipeline and the runtime skill spec lives at skills/last30days/SKILL.md.
v3 highlights in the README include shareable self-contained HTML briefs (no JS) saved to ${LAST30DAYS_MEMORY_DIR}, an "intelligent pre-research" brain that resolves the right handles/subreddits/hashtags before searching, and a humor/virality judge that adds a "Best Takes" section to every brief.
Key features (concrete)
Cross-platform signals: Reddit top comments with upvote counts (public JSON), X likes, YouTube transcripts and selected comments, TikTok/Instagram/Threads when enabled, Polymarket odds, GitHub PR/merge metrics, Digg clusters, Pinterest pins.
v3 improvements: shareable HTML briefs (/last30days OpenClaw --emit=html), cross-source cluster merging, single-pass entity-aware comparisons, auto-discovered competitor comparisons, and GitHub person-mode that reports PR velocity and release notes.
Modes: ELI5 mode for plain-language syntheses, --competitors for automated multi-entity comparisons, and --synthesis-file for converting markdown briefs to HTML.
Who it's useful for
Product managers, reporters, sales and business development reps, engineers, and anyone prepping for a meeting or launch who needs the last 30 days of signal across social and web sources. Examples in the README show practical uses: /last30days Peter Steinberger to see recent PRs and tweets; /last30days Kanye West to combine social, YouTube views, and Polymarket odds; /last30days OpenAI --competitors to produce 3-way comparisons.
Why it matters / Why it's trending now
The project just surged in attention (daily trending rank and large star gain) because v3 dramatically improves recall and relevance by resolving people/handles/communities before issuing API calls and by merging clusters across sources.
It surfaces signals other search tools miss (Polymarket odds, Reddit comment votes, YouTube transcript quotes) and produces shareable, print-friendly HTML briefs suited for Slack/Notion/ email.
Zero-config for Reddit/HN/Polymarket/GitHub and an install path for Claude Code (/plugin marketplace add mvanhorn/last30days-skill) or universal install via npx skills add mvanhorn/last30days-skill -g lower the activation friction, explaining rapid adoption.
Quick examples from README
/last30days OpenClaw --emit=html — creates a self-contained dark-mode HTML brief.
/last30days Peter Steinberger --github-user=steipete — person-mode shows merged PR stats and recent releases.
/last30days "OpenAI vs Anthropic vs xAI" — auto-discovers peers and runs parallel pipelines to produce a merged comparison.
Caveats
Some sources (TikTok, Instagram, Threads, Pinterest) require SCRAPECREATORS_API_KEY or opt-in flags; data-quality warnings are logged to stderr and do not leak into shareable artifacts.
Google aggregates editors. /last30days searches people.
You can't get this search anywhere else because no single AI has access to all of it. Google search doesn't touch Reddit comments or X posts. ChatGPT has a deal with Reddit but can't search X or TikTok. Gemini has YouTube but not Reddit. Claude has none of them natively. Each platform is a walled garden with its own API, its own tokens, its own auth. But you can bring your own keys and browser sessions, and suddenly an AI agent can search all of them at once, score them against each other, and tell you what actually matters.
That's the unlock. Not one better search engine. A dozen disconnected platforms, bridged by an agent.
/last30days Peter Steinberger
You have a meeting tomorrow. You Google them. You get their LinkedIn from 2023. /last30days gives you what they're actually doing this month: joined OpenAI to work on Codex, fighting Anthropic's ban on third-party agents, shipping 23 PRs at 85% merge rate, building "LobsterOS" for cross-device agent control, and r/ClaudeCode hit 569 upvotes debating whether he's a hero or "insufferable." Scattered across X posts, Reddit threads, YouTube transcripts, and GitHub commits. None of it was on Google.
Why this exists
I 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.
But it turned into something bigger. Now I run it before a sales call to know the last 30 days truth about a business. Before a meeting to read someone's recent tweets and podcast transcripts. Before a Disney World trip to know which rides are closed and what the community says about Genie+. Before I build anything to know what problems people are actually hitting.
If you're meeting with a CEO, have you read all their tweets and YouTube transcripts from the last 30 days? I have.
Sources, scored by the people
Source
What the people tell you
Reddit
The unfiltered take. Top comments with upvote counts, free via public JSON. The real opinions that Google buries.
X / Twitter
The hot take, the expert thread, the breaking reaction. First to know, first to argue.
YouTube
The 45-minute deep dive. Full transcripts searched for the 5 quotable sentences that matter.
TikTok
The creator reaching 3.6M people with a take you'll never find on Google.
Instagram Reels
The influencer perspective with spoken-word transcripts. The visual culture signal.
Hacker News
The developer consensus. 825 points, 899 comments. Where technical people actually argue.
Polymarket
Not opinions. Odds. Backed by real money. 96% confidence on album sales. 4% on an acquisition.
GitHub
For people: PR velocity, top repos by stars, release notes. For topics: issues and discussions.
Digg
Curated story clusters from Digg's AI 1000 leaderboard (~1000 high-signal AI accounts on X), with attributable inline quotes (no X auth required). Auto-enabled when digg-pp-cli is on PATH.
Threads
The post-Twitter text layer. Conversations from creators and brands.
Pinterest
Visual discovery. Pins, saves, and comments on products and ideas.
Bluesky
The decentralized social layer. AT Protocol posts from the post-Twitter migration.
Perplexity
Grounded web search with citations via Sonar Pro.
Web
The editorial coverage, the blog comparisons. One signal of many, not the only one.
Community contributors keep adding more. Truth Social, Xiaohongshu (RED), and others are in the engine with more on the way.
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 what's culturally relevant than a press release. Polymarket odds backed by $66K in volume are harder to argue with than a pundit's guess.
The synthesis ranks by what real people actually engaged with. Social relevancy, not SEO relevancy.
What people actually use it for
Before a meeting./last30days Peter Steinberger - joined OpenAI's Codex team, fighting Anthropic's ban on third-party agents, 23 PRs merged at 85% merge rate on GitHub, building LobsterOS for cross-device agent control. r/ClaudeCode: "Ever since OpenClaw released, it was widely known that if you run it through anything other than the API, you were gonna get banned eventually" (227 upvotes). That's not on LinkedIn.
When something drops./last30days Kanye West - UK blocked his visa, Wireless Festival canceled, sponsors fled. But BULLY debuted #2 on Billboard. Fantano came back from his "Yay sabbatical" to review it (653K views). SoFi Homecoming brought out Lauryn Hill and Travis Scott for 44 songs. Polymarket: "Will Kanye tweet again?" 86% Yes. 23 Reddit threads, 17 YouTube videos, 86K upvotes.
To compare tools./last30days OpenClaw vs Hermes vs Paperclip - "These aren't competitors, they're layers." OpenClaw is the executor (351K GitHub stars, live), Hermes is the self-improving brain (31K stars), Paperclip is the org chart (49K stars). Star counts pulled live from the GitHub API, not stale blog posts. Side-by-side table with architecture, memory, security, best-for. Per @IMJustinBrooke: "OpenClaw = Charmander, Hermes = Charizard."
To understand the world./last30days Iran vs USA - Day 38 of the war. Trump's Tuesday deadline for Iran to reopen the Strait of Hormuz. Two US warplanes downed. Oil at $126/barrel. The IEA called it "the largest supply disruption in the history of the global oil market." Polymarket: ceasefire by Dec 31 at 74%. 27 X posts, 10 YouTube videos, 20 prediction markets.
Before a trip./last30days Universal Epic Universe - Expansion already under construction. "Project 680" permit filed. Fireworks show confirmed by infrastructure but unannounced. Wait times: Mine-Cart Madness averaging 148 minutes. No annual pass yet, and locals are frustrated. Stardust Racers down for refurbishment through April 5.
To learn something fast./last30days Nano Banana Pro prompting - JSON-structured prompts are replacing tag soup. @pictsbyai's nested format prevents "concept bleeding." Edit-first workflow beats regeneration. Then it writes you a production prompt using exactly what the community said works.
What v3 Changed
Shareable HTML briefs
Ask for an HTML brief and the skill saves a self-contained, dark-mode, print-friendly file you can drop into Slack, email, or Notion. No raw markdown leaks. Inline CSS, system-font fallbacks behind Inter and JetBrains Mono. No JavaScript. Works offline.
/last30days OpenClaw --emit=html
or just ask in plain language:
/last30days OpenClaw, give me a shareable HTML brief
/last30days Cursor IDE for slack
/last30days Anthropic earnings export as html
The skill emits the synthesis in chat as usual AND saves a brief to ${LAST30DAYS_MEMORY_DIR}/{topic}-brief.html (defaults to ~/Documents/Last30Days/). The chat response ends with the file path so you can open it or drag it into a message.
What's in the file: badge, inline metadata line, the model's synthesis verbatim with all citations, the engine footer (✅ All agents reported back! tree), and a colophon noting the topic + how to re-run. Data quality warnings (degraded run, thin evidence, etc.) stay in the engine's stderr logs; they never leak into the shareable artifact.
For direct CLI use without the model in the loop, the engine also accepts --synthesis-file PATH to convert any markdown synthesis to HTML.
Intelligent search: the killer feature
The v3 engine doesn't just search for your topic. It figures out where to search before the search begins. Type "OpenClaw" and the engine resolves @steipete (Peter Steinberger, the creator), r/openclaw, r/ClaudeCode, and the right YouTube channels and TikTok hashtags - all via a new Python pre-research brain built by @j-sperling. The old engine searched keywords. The new engine understands your topic first, then searches the right people and communities.
This is why v3 finds content v2 never could. "Paperclip" resolves @dotta. "Dave Morin" resolves @davemorin plus @OpenClaw plus the TWiST podcast. "Peter Steinberger" resolves @steipete on X and steipete on GitHub. Bidirectional: person to company, product to founder, name to GitHub profile. The right subreddits, the right handles, the right hashtags - resolved before a single API call fires.
Best Takes
Reddit and X people are funny. The old engine buried their best stuff because it scored for relevance, not cleverness. v3 has a second judge that scores every result for humor, wit, and virality alongside the relevance score. Tommy Lloyd's "My Michael Jordan is Steve Kerr" scores low on relevance to "Arizona Basketball" but off the charts on fun. Now every brief ends with a "Best Takes" section - the cleverest one-liners, the most viral quotes, the reactions that make you want to share the research. Built in, not a toggle.
Cross-source cluster merging
When the same story appears on Reddit, X, and YouTube, v3 merges them into one cluster instead of showing three separate items. Entity-based overlap detection catches matches even when the titles use different words.
Single-pass comparisons
"CLI vs MCP" used to run three serial passes (12+ minutes). v3 runs one pass with entity-aware subqueries for both sides simultaneously. Same depth, 3 minutes.
Auto-discovered competitor comparisons
/last30days OpenAI --competitors tells the hosting reasoning model to discover the top 2 peers via WebSearch (Anthropic, xAI), run Step 0.55 per entity, and invoke the engine with "OpenAI vs Anthropic vs xAI" and a per-entity --competitors-plan JSON. The engine fans out 3 full pipelines in parallel, saves a *-raw.md file per entity, and merges them into a 3-way comparison. Same mechanics power /last30days "OpenAI vs Anthropic vs xAI" directly.
GitHub person-mode
When the topic is a person, the engine switches from keyword search to author-scoped queries. Instead of "who mentioned this name in an issue body," it answers: what are they shipping and where is it landing?
/last30days Peter Steinberger --github-user=steipete shows 22 PRs merged across 3 repos at 85% merge rate. Own projects with README summaries, star counts, and top feature requests. Release notes for what shipped this month. The synthesizer weaves it into the narrative alongside X posts and Reddit threads.
ELI5 mode
Say "eli5 on" after any research run. The synthesis rewrites in plain language. No jargon. Same data, same sources, same citations - just clearer. "Arizona wins by being physical" instead of "Arizona's identity is paint scoring (50%+ shooting, 9th nationally)." Say "eli5 off" to go back.
Everything else in v3
Free Reddit comments. Public JSON gives you threads + top comments with upvote counts. No API key, no ScrapeCreators. Just works.
YouTube transcripts that actually work. Widened candidate pool 3x past music videos to reach talk/review content with captions.
TikTok, Instagram, Threads. All three activate automatically once SCRAPECREATORS_API_KEY is set — same key, same per-call cost. Suppress any of them with EXCLUDE_SOURCES=tiktok,instagram,threads (any comma-separated subset).
Pinterest. Per-query opt-in (visual pins, narrow utility): the model passes --search=pinterest for the runs that need it. Requires SCRAPECREATORS_API_KEY.
YouTube + TikTok comments. Persistent opt-in via INCLUDE_SOURCES=youtube_comments,tiktok_comments because each video pulls N extra ScrapeCreators calls on top of the base search. Surface top comments with vote counts the same way Reddit does.
Perplexity Sonar. Grounded web search with citations via OpenRouter. Add OPENROUTER_API_KEY and INCLUDE_SOURCES=perplexity (it's a separate paid API — opt-in keeps you from being surprise-billed).
Polymarket noise filtering. Common-word disambiguation prevents "Apple" from matching "Will Apple release a car?"
Resilient Reddit. Timeout budgets and runtime fallback. One slow thread doesn't kill the whole run.
Fun judge v2. Humor scoring baked into the narrative. Reddit's cleverest one-liners mixed into the synthesis where they fit, not dumped in a separate section.
Polymarket odds, not dollars. The % odds are the magic. Dollar volumes removed from display.
Per-author cap. Max 3 items per author prevents any single voice from dominating your brief.
Entity disambiguation. When the engine resolves handles, the synthesis trusts them. No more Mallorca resorts winning over Washington athletic clubs.
OpenClaw first-class citizen. Auto-resolve for engine-side pre-research. Device auth for frictionless ScrapeCreators signup.
1,012 tests passing.
Install
Surface
Install
Updates
Claude Code (recommended)
/plugin marketplace add mvanhorn/last30days-skill
Auto via marketplace, or claude plugin update last30days@last30days-skill
Codex, Cursor, Copilot, Gemini CLI, GitHub Copilot, or any of 50+ Agent Skills hosts
Recommended because the Claude Code marketplace handles updates for you — the plugin cache is versioned and auto-refreshes when a new release publishes. Run claude plugin update last30days@last30days-skill to force a check.
If you'd rather use the agent-skills install path on Claude Code, that's also supported:
npx skills add mvanhorn/last30days-skill -g -a claude-code
The native plugin and the npx skills install can coexist. Note that Claude Code does not dedupe across install methods: if you have both the marketplace plugin and the npx skills copy active, /last30days will show two entries. Use one install method per machine.
Codex, Cursor, Copilot, Gemini CLI, and other Agent Skills hosts
Install via the open Agent Skills CLI — supports 50+ harnesses including codex, cursor, github-copilot, gemini-cli, claude-code, windsurf, cline, continue, roo, aider-desk, opencode, goose, and more (full list on the vercel-labs/skills repo).
npx skills add mvanhorn/last30days-skill -g
The -g (global) flag installs to your user directory so the skill is available across all projects. Without -g, npx skills installs project-locally into ./.skills/ (committed with the repo). For a research-the-world tool, global is what you want.
By default this installs for whichever harness npx skills detects. To target a specific one (or multiple):
npx skills add mvanhorn/last30days-skill -g -a codex
npx skills add mvanhorn/last30days-skill -g -a cursor
npx skills add mvanhorn/last30days-skill -g -a gemini-cli
npx skills add mvanhorn/last30days-skill -g -a codex -a cursor
Update later with:
npx skills update last30days -g
Or update everything you've installed globally via npx skills:
npx skills update -g
List and remove with npx skills list -g and npx skills remove last30days -g.
The symlink keeps the install in sync with your working tree as you edit — no re-copy needed. For claude.ai, build the .skill file from source: bash skills/last30days/scripts/build-skill.sh produces dist/last30days.skill.
Reddit (with comments), Hacker News, Polymarket, and GitHub work immediately. Zero configuration. Run /last30days once and the setup wizard unlocks more sources in 30 seconds.
Bring your own keys
These platforms don't have relationships with each other. X doesn't know what Reddit thinks. YouTube doesn't see TikTok. But you can bring your own API keys and browser tokens, and suddenly you have access to all of them at once.
On macOS you can store keys in the system Keychain instead of a .env file. The skill picks them up automatically as the lowest-priority source — .env files and process environment still win on collision.
# Interactive setup — prompts for each known key, skip with empty input
skills/last30days/scripts/setup-keychain.sh
# Or store a single key by hand
security add-generic-password -a "$USER" -s last30days-XAI_API_KEY -w "xai-..."# Inspect / clean up
skills/last30days/scripts/setup-keychain.sh --list
skills/last30days/scripts/setup-keychain.sh --delete XAI_API_KEY
Items are stored under service name last30days-<KEY> for the current user. On non-Darwin platforms the loader is a no-op, so there is no behaviour change for Linux/Windows users.
See CONFIGURATION.md for the full per-source key matrix, reasoning provider priority, and web-search backend priority.
Configuration
Two things you'll likely want to know on day one:
Where research files are saved.LAST30DAYS_MEMORY_DIR defaults to ~/Documents/Last30Days/ (Windows: C:\Users\<you>\Documents\Last30Days\). Override by setting that env var to any path in your shell, or --save-dir <path> per run. Use --save-suffix=<name> to keep multiple variations of the same topic separate (e.g. per client). Each run produces <slug>-raw[-suffix].md.
Trend monitoring across runs. The default mode produces a fresh markdown snapshot per run. To accumulate findings over time, add --store to persist into a SQLite database, then use scripts/watchlist.py for scheduled runs (with optional Slack / webhook delivery on new findings) and scripts/briefing.py for daily / weekly digests. The full cadence pattern is in CONFIGURATION.md.
Per-client wrapper scripts, custom category-peer subreddits, and the experimental beta channel for in-progress customizations are also documented in CONFIGURATION.md.
How it works
You type a topic. Person, company, product, technology, "X vs Y." Anything.
The agent resolves who matters. Finds X handles (including founders), GitHub repos, subreddits, TikTok hashtags, YouTube channels. For "Kanye West" it knows r/hiphopheads, @kanyewest, and "bully review" on YouTube. For "OpenClaw" it resolves openclaw/openclaw on GitHub and fetches live star counts.
All sources searched in parallel. Multi-query expansion. Results scored by engagement, relevance, freshness.
The depth nobody else has. Full YouTube transcripts from reaction videos. Top Reddit comments with upvote counts. TikTok captions. Polymarket odds. Not just titles and links.
Same story, merged. Wireless Festival announced on Reddit, discussed on X, ticket prices on TikTok = one cluster, not three separate items.
Synthesized into one brief. Grounded in specific data. Cited by source. Ranked by what people actually engage with. Not "here's what I found." It's "here's what matters."
Then it becomes your expert. After one run, your Claude session knows everything the community knows. Ask follow-up questions. Have it write prompts, draft emails, plan trips, architect systems - all grounded in what's real right now.
What people are saying
"I found a Claude Code skill that researches any topic across Reddit, X, YouTube, and HN from the last 30 days. Then writes the prompts for you. I've been manually searching Reddit and X for research before every piece of content I write. Tab by tab. Thread by thread. That's the part that takes 90 minutes. This eliminates it." -@itsjasonai
"This one skill replaced my entire research workflow. You give it a topic, it scrapes Reddit, X, and the web for what people are actually talking about. Not old blog posts. Real conversations from the last 30 days." -@itswilsoncharles
"5 of the 10 trending repos on GitHub today are Claude tools. #1: mvanhorn/last30days-skill" -@yieldhunter95
Open source
MIT license. No tracking. No analytics. Your research stays on your machine. 1,012 tests.
Built with Python 3.12+, yt-dlp, Node.js (vendored Bird client for X search), and ScrapeCreators API. v3 engine architecture by @j-sperling.