A local-first extraction tool for gathering structured metadata and media information from X (Twitter) without requiring official API access.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install x-research-kit
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install x-research-kit 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 X Research Kit?
The X Research Kit is a powerful utility designed for developers and researchers who need to harvest data from X (Twitter) and integrate it into their Openclaw Skills workflows. By leveraging proven local tools like yt-dlp and gallery-dl, this skill bypasses the need for costly API keys, allowing for the seamless extraction of tweet metadata, user profile timelines, and X Spaces information.
This skill is particularly effective for those performing sentiment analysis, engagement tracking, or content archival. It transforms raw, unstructured social media URLs into clean, actionable JSON data, enabling deeper insights into social trends and author influence while maintaining a privacy-conscious, local-first footprint.
X Research Kit Use Cases
- Performing competitive analysis by extracting recent posts from specific user timelines.
- Auditing engagement metrics such as views, likes, and retweets for specific high-impact tweets.
- Identifying media types and quality specs for videos or images hosted on the X platform.
- Researching X Spaces sessions to gather technical audio metadata.
- Archiving thread content and metadata for long-term research projects.
How X Research Kit Works
- The skill identifies the provided URL type, distinguishing between individual tweets, user profiles, or X Spaces.
- It executes a targeted command via yt-dlp or gallery-dl to fetch the raw JSON payload from the platform.
- The raw data is parsed to extract key fields like description, uploader_id, and engagement statistics.
- Metrics are formatted into human-readable units (e.g., K for thousands, M for millions) for clarity.
- The skill presents a structured Markdown summary or table to the user, offering follow-up analysis options.
X Research Kit Setup
To use this feature within your Openclaw Skills environment, ensure you have the required dependencies installed on your local machine:
# Install via Homebrew (macOS)
brew install yt-dlp gallery-dl
# Or install via pip
pip install yt-dlp gallery-dl
# Verify the installation
yt-dlp --version && gallery-dl --version
X Research Kit Data Schema & Taxonomy
The skill organizes extracted data into a structured format for easy ingestion. Below is the mapping for primary tweet metadata:
| Field | Source Path | Description |
|---|---|---|
| Full Text | .description |
The textual content of the post |
| Author | .uploader |
The display name of the creator |
| Engagement | .view_count, .like_count |
Quantitative reach and interaction data |
| Media | .formats[] |
Available resolutions and file extensions |
| Date | .upload_date |
Normalized YYYY-MM-DD timestamp |
X Research Kit Advanced Features
- Multi-tool fallback: Automatically suggests using gallery-dl for image-heavy posts when yt-dlp is insufficient.
- Browser Cookie Integration: Supports
--cookies-from-browserto bypass certain platform restrictions and access age-restricted content. - Bulk Timeline Extraction: Capable of flattening playlists to retrieve up to 20 recent posts from a profile in a single operation.
- Intelligent Rate Limiting: Includes guidance on spacing requests to avoid platform-level IP blocks during intensive research.
SKILL.md
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