A high-performance agentic tool for conducting deep, real-time research and sentiment analysis across X/Twitter's full archive.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install twitterapi-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 twitterapi-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 Research?
X Research is a specialized agentic tool designed to treat X/Twitter as a high-signal search engine for developers, analysts, and researchers. By utilizing the twitterapi.io backend, it provides access to the full Twitter archive, bypassing the standard 7-day limitations of basic search tools. As part of the Openclaw Skills library, it enables users to move beyond simple keyword matching by decomposing complex research questions into targeted, multi-query workflows that extract the most relevant perspectives from the global discourse.
This skill is built for technical depth, allowing the agent to follow conversation threads, analyze linked content like GitHub repositories, and filter out noise such as bot spam or low-engagement posts. It transforms fragmented social media data into structured, actionable intelligence, making it an essential component for anyone using Openclaw Skills to stay ahead of industry trends, product feedback, and cultural shifts.
X Research Use Cases
- Tracking real-time developer sentiment and feedback on new API changes or library releases.
- Conducting competitive intelligence by monitoring expert opinions on product launches and industry drama.
- Decomposing broad research topics into targeted queries to find specific technical solutions or troubleshooting tips.
- Monitoring a curated watchlist of industry leaders for automated heartbeat updates.
- Deep-diving into viral threads to extract consensus or controversial viewpoints on specific technologies.
How X Research Works
- The agent receives a research prompt and decomposes it into 3-5 specific X search operators (e.g., core keywords, expert voices, and domain-specific links).
- The CLI tool executes these searches via the twitterapi.io service, applying user-defined filters for likes, impressions, and timeframes.
- A local file-based cache with a 15-minute TTL is checked to minimize API costs and improve performance for identical queries.
- The agent iteratively follows promising conversation threads and uses external fetch tools to analyze linked technical resources.
- Results are synthesized into a themed markdown briefing, organizing disparate tweets into a cohesive report with direct source links.
X Research Setup
To begin using this skill, navigate to the local directory and ensure your API credentials are set in your environment configuration.
cd ~/clawd/skills/x-research
# Ensure TWITTERAPI_IO_KEY is defined
source ~/.config/env/global.env
You can then initiate a search using the bun runtime:
bun run x-search.ts search "AI agents" --sort likes --limit 15 --save
X Research Data Schema & Taxonomy
X Research organizes its operational data and research outputs across several key files and directories within the Openclaw Skills framework:
| Component | Path | Description |
|---|---|---|
| Watchlist | data/watchlist.json |
Persistent storage for accounts monitored during heartbeat checks. |
| Cache | data/cache/ |
Automated storage for JSON response fragments to prevent redundant API calls. |
| Research Drafts | ~/clawd/drafts/ |
Destination for generated markdown briefings and synthesized reports. |
| API Wrapper | lib/api.ts |
The core integration logic for the third-party Twitter API service. |
X Research Advanced Features
- Full-archive search capabilities that go back years, not just 7 days.
- Agentic thread-following to capture the full context of viral technical discussions.
- Advanced noise filtering heuristics to automatically exclude retweets, replies, and crypto-related spam.
- Quick mode for rapid-fire research with pre-configured filters and cost-efficiency summaries.
- Heartbeat integration for automated monitoring of high-priority accounts via the watchlist system.
SKILL.md
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