seo-dataforseoSEO keyword research using the DataForSEO API. Perform keyword analysis, YouTube keyword research, competitor analysis, SERP analysis, and trend tracking. Use when the user asks to: research keywords, analyze search volume/CPC/competition, find keyword suggestions, check keyword difficulty, analyze competitors, get trending topics, do YouTube SEO research, or optimize landing page keywords. Requires a DataForSEO API account and credentials in .env file.
Install via ClawdBot CLI:
clawdbot install adamkristopher/seo-dataforseoInstall dependencies:
pip install -r scripts/requirements.txtConfigure credentials by creating a .env file in the project root:
DATAFORSEO_LOGIN=your_email@example.com
DATAFORSEO_PASSWORD=your_api_passwordGet credentials from: https://app.dataforseo.com/api-access
| User says | Function to call |
|-----------|-----------------|
| "Research keywords for [topic]" | keyword_research("topic") |
| "YouTube keyword data for [idea]" | youtube_keyword_research("idea") |
| "Analyze competitor [domain.com]" | competitor_analysis("domain.com") |
| "What's trending?" | trending_topics() |
| "Keyword analysis for [list]" | full_keyword_analysis(["kw1", "kw2"]) |
| "Landing page keywords for [topic]" | landing_page_keyword_research(["kw1"], "competitor.com") |
Execute functions by importing from scripts/main.py:
import sys
from pathlib import Path
sys.path.insert(0, str(Path("scripts")))
from main import *
result = keyword_research("AI website builders")Every research task follows three phases:
Run API functions. Each function call hits the DataForSEO API and returns structured data.
All results automatically save as timestamped JSON files to results/{category}/. File naming pattern: YYYYMMDD_HHMMSSoperationkeyword__extra_info.json
After research, read the saved JSON files and create a markdown summary in results/summary/ with data tables, ranked opportunities, and strategic recommendations.
These are the primary functions in scripts/main.py. Each orchestrates multiple API calls for a complete research workflow.
| Function | Purpose | What it gathers |
|----------|---------|----------------|
| keyword_research(keyword) | Single keyword deep-dive | Overview, suggestions, related keywords, difficulty |
| youtube_keyword_research(keyword) | YouTube content research | Overview, suggestions, YouTube SERP rankings, YouTube trends |
| landing_page_keyword_research(keywords, competitor_domain) | Landing page SEO | Overview, intent, difficulty, SERP analysis, competitor keywords |
| full_keyword_analysis(keywords) | Strategic content planning | Overview, difficulty, intent, keyword ideas, historical volume, Google Trends |
| competitor_analysis(domain, keywords) | Competitor intelligence | Domain keywords, Google Ads keywords, competitor domains |
| trending_topics(location_name) | Current trends | Currently trending searches |
All functions accept an optional location_name parameter (default: "United States"). Most functions also have boolean flags to skip specific sub-analyses (e.g., include_suggestions=False).
For granular control, import specific functions from the API modules. See references/api-reference.md for the complete list of 25 API functions with parameters, limits, and examples.
Results auto-save to results/ with this structure:
results/
āāā keywords_data/ # Search volume, CPC, competition
āāā labs/ # Suggestions, difficulty, intent
āāā serp/ # Google/YouTube rankings
āāā trends/ # Google Trends data
āāā summary/ # Human-readable markdown summariesfrom core.storage import list_results, load_result, get_latest_result
# List recent results
files = list_results(category="labs", limit=10)
# Load a specific result
data = load_result(files[0])
# Get most recent result for an operation
latest = get_latest_result(category="labs", operation="keyword_suggestions")from main import get_recent_results, load_latest
# List recent files across all categories
files = get_recent_results(limit=10)
# Load latest result for a category
data = load_latest("labs", "keyword_suggestions")After running research, create a markdown summary document in results/summary/. Include:
Name the summary file descriptively (e.g., results/summary/ai-tools-keyword-research.md).
Generated Mar 1, 2026
A SaaS startup developing an AI website builder needs to identify high-volume, low-competition keywords to target in blog posts and landing pages. Using this skill, they can analyze keyword difficulty, search volume, and competitor rankings to prioritize content creation and improve organic search visibility.
A fitness influencer wants to optimize video titles and descriptions with trending YouTube keywords. This skill enables YouTube keyword research to find popular search terms, analyze SERP rankings for existing videos, and track trends to create content that aligns with viewer demand and boosts channel traffic.
An e-commerce store selling eco-friendly home products needs to expand its product pages with relevant keywords. By performing competitor analysis and full keyword analysis, they can discover long-tail keywords, assess intent, and optimize landing pages to attract targeted traffic and increase sales conversions.
A local restaurant aims to improve its online presence by targeting location-specific keywords like 'best pizza near me'. This skill helps analyze local search trends, track competitor domains in the area, and generate keyword suggestions to enhance local SEO efforts and drive foot traffic.
A consulting firm conducting market analysis for clients in the fintech sector uses this skill to identify trending topics and competitor keywords. By leveraging trending topics and SERP analysis, they gather insights into search behavior and competitive landscapes to inform strategic recommendations and reports.
An SEO agency uses this skill to provide keyword research and competitor analysis services to clients. By automating data collection and generating summaries, they can deliver actionable insights faster, scale their offerings, and charge for monthly SEO audits or one-time strategy reports.
A content platform integrates this skill to offer keyword suggestions and trend analysis to users creating blogs or videos. This enhances user engagement by providing data-driven content ideas, potentially driving subscription upgrades or premium feature sales based on advanced analytics.
An affiliate marketing site leverages this skill to optimize product review pages with high-converting keywords. By analyzing search volume and difficulty, they target lucrative niches, improve rankings, and increase commission earnings through better organic traffic and click-through rates.
š¬ Integration Tip
Ensure the DataForSEO API credentials are securely stored in the .env file and regularly update the skill to handle API rate limits and new features for reliable performance.
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