Back to List
Last30days-Skill: A New AI Agent Tool for Cross-Platform Research and Synthesis Across Reddit, X, and YouTube
Open SourceAI AgentsData SynthesisGitHub Trending

Last30days-Skill: A New AI Agent Tool for Cross-Platform Research and Synthesis Across Reddit, X, and YouTube

The last30days-skill project, recently updated to version 2.9.5, has emerged as a specialized AI agent capability designed for comprehensive digital research. Developed by mvanhorn and featured on GitHub Trending, this tool enables users to conduct deep-dive investigations across major social and information platforms including Reddit, X (formerly Twitter), YouTube, Hacker News, and Polymarket. The skill is designed to synthesize vast amounts of online data into well-documented summaries. With the recommendation of Claude Code and its availability on the plugin marketplace, this tool represents a significant step forward in automated information gathering and multi-source intelligence synthesis for AI-driven workflows.

GitHub Trending

Key Takeaways

  • Multi-Platform Integration: The tool supports research across diverse platforms including Reddit, X, YouTube, Hacker News, and Polymarket.
  • Automated Synthesis: It generates well-documented summaries based on real-time or recent web data.
  • Version 2.9.5 Update: The latest release is optimized for Claude Code, enhancing its utility for developers and researchers.
  • Marketplace Availability: Users can easily integrate the tool via the plugin marketplace using the identifier 'mvan'.

In-Depth Analysis

Comprehensive Cross-Platform Research Capabilities

The last30days-skill is engineered to bridge the gap between raw social data and actionable intelligence. By targeting high-velocity information hubs like Reddit, X, and Hacker News, the tool allows AI agents to tap into current public discourse and emerging trends. The inclusion of Polymarket suggests a specific utility for tracking prediction markets and sentiment-driven data, while YouTube integration provides access to video-based content insights. This multi-faceted approach ensures that the research synthesized is not limited to a single echo chamber but reflects a broad spectrum of the internet.

Synthesis and Documentation Standards

A core feature of the last30days-skill is its ability to transform fragmented data into a "well-documented summary." In an era of information overload, the value of this tool lies in its synthesis engine. Rather than merely aggregating links, it processes information to provide context and evidence-based overviews. The recommendation for use with Claude Code (v2.9.5) indicates a high level of compatibility with modern LLM-driven coding and research environments, allowing for a more seamless transition from data collection to final report generation.

Industry Impact

The release and trending status of last30days-skill highlight a growing demand for "Agentic Research" tools within the AI industry. As AI agents move beyond simple chat interfaces, the ability to autonomously browse, verify, and summarize information from specific high-value domains becomes critical. This tool lowers the barrier for developers to build research-heavy applications, potentially impacting how market research, sentiment analysis, and news aggregation are performed. By centralizing access to disparate platforms like Polymarket and HN, it sets a precedent for specialized AI skills that prioritize source-backed synthesis over generative speculation.

Frequently Asked Questions

Question: What platforms can the last30days-skill research?

It can conduct research across Reddit, X (Twitter), YouTube, Hacker News (HN), Polymarket, and general web topics.

Question: How can I add this tool to my environment?

You can add it via the plugin marketplace using the command or identifier 'mvan'.

Question: Is there a specific AI model recommended for this tool?

The documentation specifically recommends using Claude Code with version 2.9.5 of the skill for optimal performance.

Related News

Strix: The New Open-Source AI Security Tool Designed for Automated Vulnerability Discovery and Remediation
Open Source

Strix: The New Open-Source AI Security Tool Designed for Automated Vulnerability Discovery and Remediation

Strix has emerged as a significant open-source contribution to the cybersecurity landscape, specifically designed as an AI-powered hacking tool. Developed by the 'usestrix' team, the project focuses on two critical pillars of application security: identifying existing vulnerabilities and providing automated fixes. By leveraging artificial intelligence, Strix aims to streamline the security auditing process, allowing developers and security researchers to proactively secure their applications. As an open-source initiative hosted on GitHub, it invites community collaboration to enhance its detection capabilities and remediation logic. This tool represents a growing trend of integrating AI into the DevSecOps pipeline, bridging the gap between vulnerability identification and the technical implementation of security patches.

Supermemory: A High-Speed and Scalable Memory Engine and API for the AI Era
Open Source

Supermemory: A High-Speed and Scalable Memory Engine and API for the AI Era

Supermemory has emerged as a significant development in the AI infrastructure space, positioning itself as a high-speed and scalable memory engine. Designed specifically for the AI era, it functions as a specialized Memory API, aiming to provide developers and applications with efficient ways to manage and retrieve data. The project, which has gained traction on GitHub Trending, focuses on the critical need for memory scalability and speed as AI applications become increasingly complex. By offering a dedicated API for memory, Supermemory addresses the growing demand for robust backend solutions that can keep pace with the rapid processing requirements of modern artificial intelligence systems.

LiteLLM: A Unified Python SDK and AI Gateway for Seamless Integration of Over 100 LLM APIs
Open Source

LiteLLM: A Unified Python SDK and AI Gateway for Seamless Integration of Over 100 LLM APIs

LiteLLM, developed by BerriAI, has emerged as a critical tool for developers seeking to simplify the integration of diverse Large Language Models (LLMs). Functioning as both a Python SDK and a proxy server (AI Gateway), LiteLLM allows users to call over 100 different LLM APIs using the standardized OpenAI format or their native formats. The platform supports major providers including AWS Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, and NVIDIA NIM. Beyond simple connectivity, LiteLLM provides essential enterprise features such as cost tracking, security guardrails, load balancing, and comprehensive logging, making it a robust solution for managing multi-model AI infrastructures.