A comprehensive domain analysis tool providing deep insights into traffic, engagement, and global rankings using SimilarWeb data.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install similarweb-analytics
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install similarweb-analytics using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
SimilarWeb Analytics is a specialized tool integrated within Openclaw Skills that enables developers and analysts to perform high-fidelity domain research. It provides programmatic access to critical traffic data, including total visits, unique visitors, and global ranking trends. By leveraging this skill, users can bypass manual dashboard navigation and directly query marketing channel performance and geographic distribution for any public domain.
This skill is built for professional-grade market intelligence, offering up to 12 months of historical data. Whether you are conducting competitive analysis or auditing your own digital footprint, this skill provides the raw data necessary for data-driven decision making in the Openclaw Skills ecosystem.
To utilize SimilarWeb Analytics within Openclaw Skills, you must interface with the internal data API. Use the following setup in your Python environment:
# Ensure you are working within the Openclaw Skills sandbox environment
import sys
sys.path.append('/opt/.manus/.sandbox-runtime')
from data_api import ApiClient
client = ApiClient()
# You can now call various SimilarWeb endpoints using client.call_api()
The data returned by this skill is structured for easy parsing and integration into larger analytics pipelines. Key data points include:
| Component | Metrics Provided |
|---|---|
| Traffic | Total visits, unique visitors, and monthly granularity |
| Engagement | Bounce rate, pages per visit, and average duration |
| Ranking | Global rank over time |
| Sources | Organic Search, Paid Search, Direct, Email, Social, Referrals, Display Ads |
| Geography | Country-specific traffic share, rank, and engagement stats |
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