A real-time X (Twitter) search and monitoring tool for AI agents to find posts, track users, and analyze social engagement.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install desearch-x-search
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 desearch-x-search 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 Desearch X (Twitter) Search?
This skill provides AI agents with deep access to the X (Twitter) ecosystem via the Desearch API. It allows for sophisticated real-time monitoring of social trends, brand mentions, and user activities. By leveraging Openclaw Skills like this one, developers can build agents capable of fetching tweets by keywords, hashtags, or specific URLs, while applying granular filters for engagement and media type.
The integration is designed for high-performance data retrieval, supporting everything from single post lookups to full timeline analysis. It acts as a bridge for AI models to understand the current social landscape by providing structured, machine-readable tweet and user data.
Desearch X (Twitter) Search Use Cases
- Tracking real-time brand mentions or sentiment analysis on X (Twitter).
- Monitoring specific influencers or industry leaders for new posts and replies.
- Gathering social data for market research and trend analysis within the Openclaw Skills framework.
- Identifying viral content based on engagement thresholds like minimum likes or retweets.
- Building automated news feeds or social listening dashboards.
How Desearch X (Twitter) Search Works
- The AI agent authenticates with the Desearch platform using a verified API key.
- The user or a programmed workflow triggers a search or fetch request using parameters like keywords, hashtags, or usernames.
- The skill queries the Desearch API, applying advanced filters such as date ranges, language preferences, or verification status.
- Structured data representing Tweets and Users is returned to the agent in a consistent JSON format.
- The agent processes this social data to generate summaries, alerts, or insights as part of a larger Openclaw Skills automation.
Desearch X (Twitter) Search Setup
- Obtain an API key by signing up at the Desearch Console.
- Set the required environment variable to authorize your requests.
export DESEARCH_API_KEY='your-key-here'
- Ensure your local environment has the necessary scripts to execute the desearch.py commands used by Openclaw Skills.
Desearch X (Twitter) Search Data Schema & Taxonomy
The skill organizes data into two primary objects: Tweets and Users. This structure ensures that every endpoint in Openclaw Skills returns predictable metadata.
Core Entities
| Entity | Key Fields | Description |
|---|---|---|
| Tweet | id, text, created_at, like_count, media, entities | The primary content post and its engagement metrics. |
| User | id, username, followers_count, verified | Metadata regarding the account that authored the post. |
All tweet-returning endpoints share these shapes, with fields like id and text always present to ensure data integrity.
Desearch X (Twitter) Search Advanced Features
- Engagement filtering: Narrow results by minimum likes, retweets, replies, or quote counts.
- Media-specific queries: Filter posts to show only those containing videos, images, or animated GIFs.
- Cursor-based pagination: Efficiently navigate through large sets of retweeters or long reply chains.
- Timeline Analysis: Fetch full user timelines including original posts and retweets through Openclaw Skills.
- Verification Filtering: Toggle results to show only legacy verified or Twitter Blue subscribers.
SKILL.md
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