seomachine

Unified SEO data platform. Use for any SEO-related task - keyword research, performance tracking, competitor analysis, content planning, or reporting.

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Install skill "seomachine" with this command: npx skills add cdeistopened/opened-vault/cdeistopened-opened-vault-seomachine

SEOMachine

Unified SEO data platform. Use for any SEO-related task - keyword research, performance tracking, competitor analysis, content planning, or reporting.

Credentials

All credentials in vault .env file. Scripts read from environment variables:

DATAFORSEO_LOGIN, DATAFORSEO_PASSWORD GA4_PROPERTY_ID (451203520) GOOGLE_SERVICE_ACCOUNT_PATH GSC_SITE_URL (https://opened.co/) KEYWORDS_EVERYWHERE_API_KEY

DO NOT hardcode credentials in scripts.

Tool Map

Scripts (Ready-to-Run)

Script Purpose Command

weekly_seo_report.py

Full performance report python3 scripts/weekly_seo_report.py --domain opened.co

content_brief_generator.py

Competitor-informed brief python3 scripts/content_brief_generator.py "keyword"

competitor_gap_finder.py

Keywords we're missing python3 scripts/competitor_gap_finder.py --competitor domain.com

Modules (Import for Custom Queries)

Module Class Key Methods

dataforseo.py

DataForSEO

get_keyword_ideas() , get_serp_data() , get_questions() , analyze_competitor()

google_analytics.py

GoogleAnalytics

get_top_pages() , get_declining_pages() , get_page_trends() , get_traffic_sources()

google_search_console.py

GoogleSearchConsole

get_keyword_positions() , get_quick_wins() , get_low_ctr_pages() , get_page_performance()

data_aggregator.py

DataAggregator

identify_content_opportunities() , generate_performance_report() , get_priority_queue()

keyword_analyzer.py

KeywordAnalyzer

Keyword clustering, difficulty analysis

search_intent_analyzer.py

SearchIntentAnalyzer

Classify search intent

seo_quality_rater.py

SEOQualityRater

Score content for SEO

content_length_comparator.py

ContentLengthComparator

Compare to competitors

hubspot.py

HubSpot

Email/contact data

meta.py

Meta

Facebook/Instagram metrics

youtube.py

YouTube

YouTube analytics

webflow.py

Webflow

CMS publishing

keywords_everywhere.py

KeywordsEverywhere

Related keywords, PASF, volume, backlinks, domain keywords

References

File Content

references/seo-guidelines.md

SEO best practices

references/target-keywords.md

Priority keyword list

references/internal-links-map.md

Internal linking structure

Common Tasks

"What keywords should we target?"

Generate content brief with keyword cluster

python3 .claude/skills/seomachine/scripts/content_brief_generator.py "homeschool curriculum"

Find gaps vs competitors

python3 .claude/skills/seomachine/scripts/competitor_gap_finder.py --batch --min-volume 200

"How is our content performing?"

Full weekly report

python3 .claude/skills/seomachine/scripts/weekly_seo_report.py --domain opened.co --output markdown

"What's ranking/trending?"

Custom query using modules

import sys sys.path.insert(0, ".claude/skills/seomachine/modules") from google_search_console import GoogleSearchConsole

gsc = GoogleSearchConsole() quick_wins = gsc.get_quick_wins(days=28) # Keywords at position 11-20 trending = gsc.get_trending_queries() # Rising searches

"What content needs refresh?"

from google_analytics import GoogleAnalytics

ga = GoogleAnalytics() declining = ga.get_declining_pages(comparison_days=30, threshold_percent=-20)

"Combined analysis"

from data_aggregator import DataAggregator

agg = DataAggregator() opportunities = agg.identify_content_opportunities()

Returns: quick_wins, declining_content, low_ctr, trending_topics

Script Details

weekly_seo_report.py

Generates comprehensive weekly SEO report.

Console output

python3 scripts/weekly_seo_report.py --domain opened.co

Markdown output

python3 scripts/weekly_seo_report.py --domain opened.co --output markdown

Save to file

python3 scripts/weekly_seo_report.py --domain opened.co --output markdown --save report.md

Skip history tracking (dry run)

python3 scripts/weekly_seo_report.py --domain opened.co --no-history

Output includes:

  • Priority keyword tracking (from PRIORITY_KEYWORDS dict)

  • Quick wins (position 11-20)

  • Declining content alerts

  • Keyword opportunities

  • Week-over-week changes

content_brief_generator.py

Generates competitor-informed content brief.

python3 scripts/content_brief_generator.py "keyword phrase" python3 scripts/content_brief_generator.py "waldorf vs montessori" --scrape-top-n 10

Output includes:

  • Primary keyword metrics (volume, CPC, competition)

  • Secondary keyword cluster (top 20)

  • Top 10 SERP results

  • Competitor H2/H3 structure (scraped)

  • FAQ questions to answer

  • Recommended word count

  • Differentiation opportunities

competitor_gap_finder.py

Finds keywords competitors rank for that we don't.

Single competitor

python3 scripts/competitor_gap_finder.py --competitor cathyduffy.com --min-volume 200

Batch (default competitor set)

python3 scripts/competitor_gap_finder.py --batch --min-volume 100

With keyword limit (cost control)

python3 scripts/competitor_gap_finder.py --competitor hslda.org --max-keywords 500

Module API Reference

DataForSEO

from dataforseo import DataForSEO dfs = DataForSEO()

Keyword research

ideas = dfs.get_keyword_ideas("homeschool", limit=100) questions = dfs.get_questions("homeschool curriculum", limit=50)

SERP analysis

serp = dfs.get_serp_data("best homeschool curriculum")

Returns: search_volume, cpc, competition, organic_results, features

Check rankings

rankings = dfs.get_rankings(domain="opened.co", keywords=["homeschool", "virtual school"])

Competitor analysis

comparison = dfs.analyze_competitor("cathyduffy.com", keywords=["curriculum reviews"])

Domain metrics

metrics = dfs.get_domain_metrics("opened.co")

GoogleAnalytics

from google_analytics import GoogleAnalytics ga = GoogleAnalytics()

Top pages

top = ga.get_top_pages(days=30, limit=20, path_filter="/blog/")

Traffic trends for specific page

trends = ga.get_page_trends("/blog/waldorf-vs-montessori", days=90)

Declining content

declining = ga.get_declining_pages(comparison_days=30, threshold_percent=-20)

Traffic sources

sources = ga.get_traffic_sources(days=30)

GoogleSearchConsole

from google_search_console import GoogleSearchConsole gsc = GoogleSearchConsole()

Current rankings

positions = gsc.get_keyword_positions(days=28)

Quick wins (position 11-20, high impressions)

quick_wins = gsc.get_quick_wins(days=28)

Low CTR opportunities

low_ctr = gsc.get_low_ctr_pages(days=28)

Page performance

perf = gsc.get_page_performance("/blog/waldorf-vs-montessori", days=28)

Trending queries

trending = gsc.get_trending_queries()

DataAggregator

from data_aggregator import DataAggregator agg = DataAggregator()

All opportunities in one call

opportunities = agg.identify_content_opportunities(days=30)

Returns dict with: quick_wins, declining_content, low_ctr, trending_topics

Full performance report

report = agg.generate_performance_report(days=30)

Priority task queue

tasks = agg.get_priority_queue(limit=10)

Comprehensive page analysis

page_data = agg.get_comprehensive_page_performance("/blog/article", days=30)

Keywords Everywhere

from keywords_everywhere import KeywordsEverywhere ke = KeywordsEverywhere()

Check credits

credits = ke.get_credits()

Keyword data (volume, CPC, competition, trends) - up to 100 per call, auto-batches

data = ke.get_keyword_data(["homeschool curriculum", "virtual school", "montessori"])

Related keywords (builds topical clusters)

related = ke.get_related_keywords("homeschool curriculum")

People Also Search For (user intent paths, FAQ ideas)

pasf = ke.get_pasf_keywords("homeschool curriculum")

Full keyword universe from seeds (related + PASF, deduplicated, sorted by volume)

universe = ke.keyword_universe(["homeschool", "virtual school", "open education"])

Domain keywords (what a domain ranks for)

comp_kws = ke.get_domain_keywords("cathyduffy.com")

URL-level keywords

url_kws = ke.get_url_keywords("https://opened.co/blog/best-homeschool-math-curriculum")

Traffic estimates

traffic = ke.get_domain_traffic(["opened.co", "cathyduffy.com", "hslda.org"])

Backlinks

backlinks = ke.get_domain_backlinks("cathyduffy.com") unique_backlinks = ke.get_unique_domain_backlinks("cathyduffy.com")

Competitor keyword overlap (finds gaps and shared keywords)

overlap = ke.competitor_keyword_overlap( "opened.co", ["cathyduffy.com", "thehomeschoolmom.com", "hslda.org"] )

Cost: 1 credit per keyword. $10 = 100K credits. Auto-batches >100 keywords.

Best combos with DataForSEO:

  • KE keyword_universe() for seed expansion → DFS get_serp_data() for difficulty + SERP features

  • KE get_pasf_keywords() for FAQ content ideas → DFS get_rankings() to check current position

  • KE competitor_keyword_overlap() for gap finding → DFS analyze_competitor() for ranking comparison

Notes

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