last30days for Openclaw

A real-time research tool that extracts data from X, YouTube, and the web to generate AI-synthesized briefings and prompts.

ralph-oei
v1.0.0
Feb 17, 2026
0
852
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install last30days-gemini

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install last30days-gemini using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is last30days?

last30days is a high-performance research utility specifically optimized for Openclaw Skills to bridge the gap between real-time data collection and AI-driven analysis. It allows developers and researchers to scrape the most relevant discussions, recommendations, and debates from the last 30 days across X (Twitter), YouTube transcripts, and the web via the Brave Search API. This skill is particularly valuable for users who need to stay updated on fast-moving topics without manual searching.

By leveraging this tool within the Openclaw Skills ecosystem, you can automate the discovery of current trends and synthesize them into structured reports. The skill doesn't just return links; it gathers the context needed for Gemini to generate expert-level briefings and copy-paste prompts, making it an essential asset for modern AI workflows.

last30days Use Cases

  • Tracking real-time sentiment and discussions on X regarding new product launches.
  • Summarizing key insights from the latest YouTube videos in a specific niche.
  • Researching current market trends to inform digital marketing strategies.
  • Automated generation of context-rich prompts for LLM applications.

How last30days Works

  1. The skill authenticates with social and search providers using environment variables like BRAVE_API_KEY and X tokens.
  2. It executes a broad search query across three primary channels: X, YouTube, and Brave Search.
  3. The engine parses transcripts from YouTube using yt-dlp and scrapes social threads to build a comprehensive dataset.
  4. Users can choose an output format—JSON, Markdown, or Compact—depending on whether the data is for human consumption or AI processing.
  5. Optionally, the JSON output is piped to Gemini for high-level synthesis and briefing generation.

last30days Setup

Configure your environment variables and create the necessary directory structure for the skill:

# Export required tokens
export AUTH_TOKEN=your_x_auth_token
export CT0=your_x_ct0_token
export BRAVE_API_KEY=your_brave_key

# Initialize configuration
mkdir -p ~/.config/last30days
cat > ~/.config/last30days/.env << 'EOF'
BRAVE_API_KEY=your_key_here
EOF

last30days Data Schema & Taxonomy

The skill organizes research data based on the source and the requested output format. Below is the structure used for data aggregation:

Source Method Data Type
X/Twitter Bird CLI / Cookies Social threads and mentions
YouTube yt-dlp Video transcripts and metadata
Web Brave API Search engine results and snippets

The structured JSON output is specifically designed for integration with Openclaw Skills and AI models like Gemini 2.0 Flash.

last30days Advanced Features

  • Integrated Gemini synthesis for automated expert briefings.
  • Multi-source triangulation (X + YouTube + Web) for more accurate research.
  • Low-latency 'Quick Mode' for rapid high-level analysis.
  • Flexible output emitters including --emit=json for programmatic piping into other Openclaw Skills.

SKILL.md


Loading

Related Openclaw Skills

METADATA

Github Stars: 0
forks: 0

Featured*