An advanced research tool that enables AI agents to perform deep-dive analysis of X/Twitter trends, user activity, and niche community conversations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install x-research-skill
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-skill 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/Twitter Research Skill?
The X/Twitter Research skill provides a robust interface for AI agents to interact with the twitterapi.io service, allowing for sophisticated data mining across the platform. As a key component of the Openclaw Skills library, it empowers developers to build agents that can monitor market sentiment, track influencer activity, and identify emerging opportunities in real-time. By automating the retrieval of tweets, user profiles, and trending topics, this skill eliminates the manual overhead of social media monitoring.
Built for high-performance research, it supports complex query operators and structured data extraction. Whether you are tracking the latest blockchain developments or monitoring brand mentions, integrating this into your Openclaw Skills setup ensures your agent has access to the most current public discourse available on the social web.
X/Twitter Research Skill Use Cases
- Generating automated daily trend reports for specific ecosystems like Solana or DeFi.
- Monitoring key industry leaders and official accounts for breaking announcements.
- Conducting competitive analysis by tracking mentions and sentiment around specific projects.
- Identifying developer pain points and product gaps by searching for specific technical complaints.
How X/Twitter Research Skill Works
- The agent initializes the session by loading the API credentials from the local secrets directory.
- Advanced search queries are executed using specific operators to filter for high-impact content.
- The skill fetches metadata including tweet content, engagement metrics, and user profile information.
- Data is processed through a research workflow that categorizes findings into verticals like Infrastructure, DeFi, or AI.
- A final markdown report is generated and saved to the local workspace for human or agent review.
X/Twitter Research Skill Setup
To get started with this addition to your Openclaw Skills, ensure your API key is stored correctly:
# Create the secrets directory if it doesn't exist
mkdir -p ~/.openclaw/secrets
# Store your API key
echo "export TWITTERAPI_KEY='your_api_key_here'" > ~/.openclaw/secrets/twitterapi.env
# Load the environment variable
source ~/.openclaw/secrets/twitterapi.env
You can test the connection by running a simple trend search:
curl -s "https://api.twitterapi.io/twitter/trends" -H "X-API-Key: $TWITTERAPI_KEY"
X/Twitter Research Skill Data Schema & Taxonomy
The skill generates structured research reports located at workspace/research/solana-trends-YYYY-MM-DD-HH.md. The data is organized into the following taxonomy:
| Section | Content Description |
|---|---|
| Hot Topics | A list of currently trending keywords and hashtags identified via the API. |
| Key Tweets | Notable posts with high engagement, including direct links for verification. |
| Pain Points | Aggregated user complaints or technical hurdles mentioned in the search results. |
| Ideas | Potential project opportunities or feature requests inferred from community discussions. |
| By Vertical | Data grouped by specific categories such as Payments, Gaming, or Infrastructure. |
X/Twitter Research Skill Advanced Features
- Granular filtering using advanced operators like min_faves, exclusions, and exact phrase matching.
- Support for pagination via cursors to handle large volumes of research data efficiently.
- Multi-account monitoring workflows to track entire ecosystems simultaneously.
- Vertical-specific search templates optimized for technical and financial research.
- Cost-effective data retrieval with transparent per-request pricing models.
SKILL.md
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