Jonathon's AI Wiki

last30days-skill (Multi-Platform Research Skill)

4 min read

Source: Mvanhorn Last30Days Skill 2026 04 27

last30days-skill (Matt Van Horn, github.com/mvanhorn/last30days-skill) is a Claude/Codex/Hermes skill that aggregates current information about any topic from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the open web — then ranks results by real engagement metrics (upvotes, likes, views, money on Polymarket) instead of editorial curation. Type /last30days <topic> and it returns a research brief based on what people actually engaged with in the last 30 days. MIT, 24.2k GitHub stars, 1,012 passing tests, Python 3.12+, current version 3.0.14.

Key Takeaways

  • Pre-research brain (v3 engine). Resolves the topic to relevant people, communities, and hashtags before the API calls fire. “Kanye West” maps to r/hiphopheads, @kanyewest, the right YouTube review channels and TikTok hashtags. v3 architecture by @j-sperling.
  • Multi-source scoring. Ranks by upvotes, likes, views, and Polymarket odds — including real money backing. Merges duplicate stories across platforms into single clusters and filters to the last 30 days only.
  • Synthesis features. Pulls full YouTube transcripts and Reddit comment threads with engagement counts. “Best Takes” section highlights viral quotes. Per-author caps prevent any single voice from dominating. ELI5 mode produces plain-language explanations.
  • Comparison mode. A topic containing “vs”/“versus” or the --competitors flag runs N parallel pipelines for multi-way comparison. --competitors auto-discovers peers via the hosting reasoning model’s WebSearch (Claude Code, Codex, Hermes, Gemini); engine flag mode is kept for headless/cron use. Per-entity sub-runs each produce their own slug-raw.md with a Resolved Entities block.
  • Zero-config defaults. Works immediately against Reddit, Hacker News, Polymarket, and GitHub (free public data). Optional sources unlock with keys/setup: X/Twitter (browser login), YouTube (yt-dlp install), TikTok/Instagram/Threads/Pinterest (ScrapeCreators API), Perplexity Sonar (OpenRouter key), Brave Search.
  • Multi-runtime. Distributes as a Claude Code plugin, an OpenClaw skill, a .skill upload for Claude.ai, and a manual clone. Same engine across runtimes.
  • Privacy stance. No tracking, no analytics — research stays on the local machine. MIT licensed.

Implementation

Tool/Service: last30days-skill v3.0.14 (mvanhorn/last30days-skill, MIT)

Setup (Claude Code):

/plugin marketplace add mvanhorn/last30days-skill

Setup (OpenClaw):

clawhub install last30days-official

Setup (Claude.ai web): Download the .skill bundle from the repo’s releases tab, then upload via Settings → Capabilities → Custom skills.

Setup (manual / dev): Clone the repo, install Python 3.12+, optionally install yt-dlp for YouTube transcripts and add API keys for the optional sources you want.

Cost: Free skill. Optional API costs: ScrapeCreators (per-call), OpenRouter (Perplexity Sonar usage), Brave Search (free tier available). Reddit / HN / Polymarket / GitHub are zero-cost.

Integration notes:

  • The skill is built on top of yt-dlp for YouTube transcript and metadata extraction. Install yt-dlp first if YouTube coverage matters.
  • Pre-research relies on the hosting model’s WebSearch. Works best where the host has a real search tool configured (Claude Code with WebSearch, Codex, Hermes).
  • v3.0.13+ supports the --competitors-plan JSON flag for handing the engine a per-entity plan (X handle, related accounts, subreddits, GitHub user/repos, context) so the hosting model can drive discovery and the engine just executes the fanout.

Try It

  • Run /last30days Claude Code for an engagement-ranked snapshot of what people are actually saying about Claude Code right now — verify against your own intuition.
  • Use /last30days OpenAI vs Anthropic vs xAI to test comparison mode; check whether the auto-discovered peers match your mental model and whether the synthesis surfaces non-obvious differences.
  • Pair with [[claude-ai/social-media-skills-charlie-hills|social-media-skills]] for a “research → write” pipeline: last30days for what to talk about, social-media-skills for the post itself.
  • Add the skill on a research-focused machine where yt-dlp and ScrapeCreators are configured — so YouTube and TikTok actually return data.

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