Back to list
Last30days-Skill: A New AI Agent Tool for Synthesizing Real-Time Trends Across Major Social Platforms
Open SourceAI AgentsClaude CodeData Synthesis

Last30days-Skill: A New AI Agent Tool for Synthesizing Real-Time Trends Across Major Social Platforms

The open-source community has introduced 'last30days-skill' (v2.9.5), a specialized AI agent skill designed to research and synthesize information from across the digital landscape. Developed by mvanhorn and featured on GitHub Trending, this tool allows users to analyze topics across Reddit, X (formerly Twitter), YouTube, Hacker News (HN), and Polymarket. By integrating with Claude Code, the skill enables the creation of reliable summaries from diverse web sources. This release represents a significant step in cross-platform data synthesis, providing a streamlined way to track recent trends and discussions within a single AI-driven workflow available via the plugin marketplace.

GitHub Trending

Key Takeaways

  • Multi-Platform Research: Capability to research topics across Reddit, X, YouTube, Hacker News, and Polymarket.
  • Synthesis Engine: Focuses on generating reliable summaries from diverse web-based information sources.
  • Claude Code Integration: Version 2.9.5 is specifically recommended for use with Claude Code.
  • Easy Accessibility: Available through the plugin marketplace by adding 'mvan'.

In-Depth Analysis

Cross-Platform Intelligence Gathering

The 'last30days-skill' serves as a specialized bridge between AI agents and the most active hubs of public discourse. By targeting platforms like Reddit, X, and Hacker News, the tool captures real-time sentiment and technical discussions. The inclusion of Polymarket suggests a focus on prediction markets and current events, while YouTube integration allows for the synthesis of video-based content. This multi-faceted approach ensures that the AI agent can look beyond static search results to find what is currently trending or being debated in specialized communities.

Integration with Claude Code

A significant feature of the v2.9.5 update is its optimization for Claude Code. By recommending this specific version for Claude's coding and automation environment, the developer enables a more seamless research-to-output pipeline. Users can add the skill via the plugin marketplace using the identifier 'mvan', allowing the AI to pull in external context without leaving the development or research environment. This integration highlights the growing trend of modular AI skills that can be plugged into existing large language model (LLM) frameworks to extend their native capabilities.

Industry Impact

The release of 'last30days-skill' underscores the industry's shift toward specialized, agentic tools that handle the 'heavy lifting' of data collection and summarization. For the AI industry, this signifies a move away from general-purpose chatbots toward targeted agents that can navigate specific web architectures (like those of social media and prediction markets). By providing a reliable way to synthesize information from the last 30 days, this tool addresses the 'recency gap' often found in static AI models, offering a practical solution for users who require up-to-the-minute situational awareness across multiple digital channels.

Frequently Asked Questions

Question: Which platforms can the last30days-skill research?

It can research and synthesize information from Reddit, X (Twitter), YouTube, Hacker News (HN), Polymarket, and general web topics.

Question: How do I install this AI agent skill?

Users can add the skill through the plugin marketplace by searching for or adding 'mvan'.

Question: What is the recommended environment for version 2.9.5?

Version 2.9.5 is specifically recommended for use with Claude Code to achieve optimal results in research and summarization tasks.

Related News

DeskcommCRM Emerges as an Open-Source AI Sales Operating System and WhatsApp CRM Alternative
Open Source

DeskcommCRM Emerges as an Open-Source AI Sales Operating System and WhatsApp CRM Alternative

DeskcommCRM has been introduced by developer melgarafael as a self-hosted, open-source AI sales operating system tailored specifically for conversational commerce. Built as an open-source alternative to established proprietary platforms such as Kommo, Octadesk, and Intercom, the solution centers on businesses that execute sales workflows directly through chat interfaces. Core technical highlights include native AI Agent functionality, WhatsApp connectivity powered by WAHA, and integration readiness through the Model Context Protocol (MCP). To address enterprise and organizational demands, DeskcommCRM natively incorporates multi-tenant architecture alongside compliance support for Brazil's General Data Protection Law (LGPD). By combining chat-first sales tooling with self-hosting flexibility and AI orchestration, DeskcommCRM delivers an open alternative to proprietary customer relationship management ecosystems.

Open Source GitHub Repository Compiles Extracted System Prompts Across Major Models from Anthropic, OpenAI, and Google
Open Source

Open Source GitHub Repository Compiles Extracted System Prompts Across Major Models from Anthropic, OpenAI, and Google

A newly trending GitHub repository titled system_prompts_leaks, maintained by developer asgeirtj, has compiled extracted system prompts from leading artificial intelligence models and developer platforms. The repository aggregates system-level instructions from prominent organizations including Anthropic, OpenAI, Google, xAI, Cursor, and Kimi. Featured systems span Anthropic's Claude Fable 5.1, Opus 5, Claude Design, and Claude Code; OpenAI's ChatGPT GPT-6-Astra and Codex; Google's Gemini 3.8 Flash, 3.1 Pro, and Antigravity; and xAI's Grok and Grok Bot. According to the repository maintainer, the collection is maintained with regular updates to track prompt configurations across these diverse conversational and specialized developer models. The repository has quickly gained visibility among researchers, prompt engineers, and AI practitioners studying model alignment, system behavior, and instruction-tuning patterns across commercial generative artificial intelligence systems.

MathModelAgent Hits GitHub Trending: Autonomous AI Agent Streamlines Mathematical Modeling and Academic Paper Generation
Open Source

MathModelAgent Hits GitHub Trending: Autonomous AI Agent Streamlines Mathematical Modeling and Academic Paper Generation

MathModelAgent, an open-source AI project developed by jihe520, has surged onto GitHub Trending by delivering an end-to-end autonomous solution for mathematical modeling. Designed specifically as an intelligent agent equipped with specialized operational skills, the system automates the complete mathematical modeling lifecycle—from initial problem analysis and quantitative model construction to code execution and documentation. The tool culminates in generating a fully formatted, submission-ready paper without requiring extensive manual drafting. By integrating multi-step problem solving with publication-level writing, MathModelAgent highlights the growing potential of agentic AI systems within academic and scientific domains. The project offers a practical demonstration of how targeted agent skills can eliminate repetitive operational bottlenecks in complex mathematical analysis and research documentation.