Dataforseo Skill Claude

Abstract

1. Introduction

A Claude Code skill that provides complete DataForSEO API integration for SEO data and analysis.

2. Objective

DataForSEO API skill for Claude Code - Complete SEO data integration

This project demonstrates how Python can be applied to a real-world Digital Marketing & SEO problem.

3. Key Features / Modules

• Keyword Research: Search volume, CPC, competition, keyword ideas
• SERP Analysis: Google, Bing, YouTube organic results
• Backlink Analysis: Profile overview, referring domains, anchors
• Competitor Analysis: Domain intersection, keyword gap, competing domains
• Technical SEO: Page audits, Lighthouse scores, technology detection
• Content Analysis: Brand mentions, sentiment analysis
• Trends: Google Trends data
• And more: Business data, merchant data, app store data, AI optimization

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/nikhilbhansali/dataforseo-skill-claude.git
cd dataforseo-skill-claude

1. Copy the dataforseo folder to ~/.agents/skills/:
2. Create symlink in Claude skills directory:
3. Restart Claude Code

cp -r dataforseo ~/.agents/skills/

ln -sf ../../.agents/skills/dataforseo ~/.claude/skills/dataforseo

import sys, os
sys.path.insert(0, os.path.expanduser('~/.agents/skills/dataforseo/scripts'))
from dataforseo_client import save_credentials, verify_credentials

# Get your credentials from https://app.dataforseo.com/
login = "your_email@example.com"
password = "your_api_password"

if verify_credentials(login, password):
    save_credentials(login, password)
    print("Credentials saved!")

import sys, os
sys.path.insert(0, os.path.expanduser('~/.agents/skills/dataforseo/scripts'))
from dataforseo_client import keywords_search_volume, extract_results, to_csv

# Get search volume for keywords
response = keywords_search_volume(
    keywords=["seo tools", "keyword research"],
    location_name="United States"
)
results = extract_results(response)
csv_path = to_csv(results, "keyword_volumes")
print(f"Results saved to: {csv_path}")

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by nikhilbhansali and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.