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This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
Problem solved
Traditional search engines like Google aggregate editorially ranked content, while individual AI models have limited access to specific platforms (e.g., ChatGPT has Reddit but not X). /last30days solves this by giving an AI agent simultaneous access to multiple disconnected platforms, scoring content by real user engagement (upvotes, likes, money) rather than editorial curation.
Deployment reality
The available setup signal starts with: npx skills add mvanhorn/last30days-skill -g. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build agents that research people, companies, or topics by aggregating real-time social signals from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and more. Use cases include pre-meeting intelligence (reading a CEO's recent tweets and podcast transcripts), competitive analysis, tracking community sentiment on products, and discovering breaking trends before they appear on Google. The ceiling includes any scenario where understanding current public discourse across multiple platforms is valuable.
Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.
mvanhorn/last30days-skill is tracked as a Python project in the AI Agent, LLM Tool area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 57k total stars, with +206 today, +0 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Active; the latest push was 21 days ago, and the open issue queue is 96, about 0.17% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 5.0k forks and 57k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need Python teams evaluating ecosystem-native tooling. Be cautious when you need a legal review, security audit, or production SLA.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 2.7k. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyMIT is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
57k Stars
Reuse
5.0k Forks
Attention
57k Watchers
Maintenance
active
License
MIT
Open issues
96
/last30days is an AI agent-led search engine that searches across multiple social platforms (Reddit, X, YouTube, TikTok, etc.) and scores results by real user engagement (upvotes, likes, Polymarket odds) rather than editorial curation. It synthesizes a brief of what people are actually discussing and engaging with in the last 30 days.
Key Features
- Searches 15+ sources (Reddit, X, YouTube, TikTok, GitHub, Polymarket, etc.) in parallel, scoring by real engagement metrics like upvotes, likes, and betting odds. - Zero-config setup with a wizard to unlock additional sources; works with Claude Code, Codex, Cursor, Copilot, and 50+ Agent Skills hosts. - AI agent judge synthesizes all signals into a single brief, giving you what people are actually doing and saying, not what editors or SEO rank.
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
LLM Tool
Libraries and tools for LLM apps, RAG, prompts, and evals
npx skills add mvanhorn/last30days-skill -g80
Health Score
Active
Commit Activity
Jan 23, 2026
Created
Aug 2, 2026
Last push
+652
Today's growth
+2.7k
7-day growth
+2.7k
30-day growth
Forks
Open
Watchers
mvanhorn
GitHub profileobra/superpowers
An agentic skills framework & software development methodology that works.
affaan-m/ECC
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
NousResearch/hermes-agent
The agent that grows with you
mattpocock/skills
Skills for Real Engineers. Straight from my .agents directory.
multica-ai/andrej-karpathy-skills
A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.
✓
License
✓
Forked
✓ Active
Maintained
Problem Solved
Traditional search engines like Google aggregate editorially ranked content, while individual AI models have limited access to specific platforms (e.g., ChatGPT has Reddit but not X). /last30days solves this by giving an AI agent simultaneous access to multiple disconnected platforms, scoring content by real user engagement (upvotes, likes, money) rather than editorial curation.
Capabilities
Developers can build agents that research people, companies, or topics by aggregating real-time social signals from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and more. Use cases include pre-meeting intelligence (reading a CEO's recent tweets and podcast transcripts), competitive analysis, tracking community sentiment on products, and discovering breaking trends before they appear on Google. The ceiling includes any scenario where understanding current public discourse across multiple platforms is valuable.
Bottom Line
This skill is ideal for developers and professionals who need real-time, multi-platform social intelligence—especially for staying ahead in fast-moving fields like AI, tech, or business. It should be avoided by those who require only traditional web search or have privacy concerns about aggregating public data. The key trade-off is convenience and breadth of access versus reliance on third-party API keys and browser sessions for some sources.