Imported from seranking/seo-skills (skills/seo-google/SKILL.md). Install upstream with npx skills add seranking/seo-skills --skill seo-google. Copyright stays with the author.

Example output: examples/seo-google-quickstart-20260514/README.md

Google SEO APIs

Direct access to Google's own SEO data. Bridges the gap between crawl-based analysis (the rest of the catalogue) and Google's real-time field data: actual Chrome user metrics, real indexation status, search performance, and organic traffic.

All APIs are free. Setup requires a Google Cloud project with API key and/or service account — run the setup command for step-by-step instructions, or read references/auth-setup.md directly.

Adapted from AgriciDaniel/claude-seo's seo-google skill (MIT). Scripts, references, and command surface mirror the upstream implementation. Config path namespaced to ~/.config/seo-skills/ for clean coexistence with the original.

Prerequisites

• Required: Python 3.10+ and the Google API client libraries. Install via bash extensions/google/install.sh.
• Required: at minimum a Google API key (Tier 0). For full coverage, also a Google Cloud service account (Tier 1+) and optionally a GA4 property ID (Tier 2) and Google Ads developer token (Tier 3).
• Config file: ~/.config/seo-skills/google-api.json.

Before executing any command, check credentials:

python scripts/google_auth.py --check --json

Config file shape (~/.config/seo-skills/google-api.json):

{
  "service_account_path": "/path/to/service_account.json",
  "api_key": "AIzaSy...",
  "default_property": "sc-domain:example.com",
  "ga4_property_id": "properties/123456789"
}

If missing, read references/auth-setup.md and walk the user through setup.

Credential Tiers

Always communicate the detected tier before running commands.

Quick Reference

PageSpeed + CrUX

pagespeed <url>

Combined Lighthouse lab data + CrUX field data.

Script: python scripts/pagespeed_check.py <url> --json Reference: references/pagespeed-crux-api.md Default: Both mobile + desktop strategies, all Lighthouse categories.

Output merges lab scores (point-in-time Lighthouse) with field data (28-day Chrome user metrics). CrUX tries URL-level first, falls back to origin-level.

crux <url>

CrUX field data only (no Lighthouse run). Faster.

Script: python scripts/pagespeed_check.py <url> --crux-only --json

crux-history <url>

25-week CrUX History trends. Shows whether CWV metrics are improving, stable, or degrading.

Script: python scripts/crux_history.py <url> --json Reference: references/pagespeed-crux-api.md

Output includes per-metric trend direction, percentage change, and weekly p75 values.

Search Console

gsc <property>

Search Analytics: clicks, impressions, CTR, position for last 28 days.

Script: python scripts/gsc_query.py --property <property> --json Reference: references/search-console-api.md Default: 28 days, dimensions=query,page, type=web, limit=1000.

Includes quick-win detection: queries at position 4-10 with high impressions.

Filtering: --device {desktop,mobile,tablet}, --country <ISO3>, --page <url-or-substring> (defaults to contains match; pass --page-match equals for exact-URL match). Combine for per-URL query analysis: --page /blog/best-ai-seo-tools/ --dimensions query.

AI Overview / AI Mode: --ai-overview (or --ai-mode) filters results to queries where Google rendered an AI Overview / AI Mode SERP that included one of your URLs. This is Google's first-party answer to "are we cited in AI Overview?" — clicks, impressions, CTR, and avg position straight from GSC. Combine with --dimensions query,page to see which queries+pages earned AI Overview presence, or with --page /post/ to scope to one URL. For other appearance types (RICH_RESULT, REVIEW_SNIPPET, etc.) use --search-appearance <value>.

inspect <url>

URL Inspection: real indexation status from Google.

Script: python scripts/gsc_inspect.py <url> --json

Returns: verdict (PASS/FAIL), coverage state, robots.txt status, indexing state, page fetch state, canonical selection, mobile usability, rich results.

inspect-batch <file>

Batch inspection from a file (one URL per line). Rate limited to 2,000/day per site.

Script: python scripts/gsc_inspect.py --batch <file> --json

sitemaps <property>

List submitted sitemaps with status, errors, warnings.

Script: python scripts/gsc_query.py sitemaps --property <property> --json

Indexing API

index <url>

Notify Google of a URL update.

Script: python scripts/indexing_notify.py <url> --json Reference: references/indexing-api.md

The Indexing API is officially for JobPosting and BroadcastEvent/VideoObject pages. Always inform the user of this restriction. Daily quota: 200 publish requests.

index-batch <file>

Batch submit URLs from a file. Tracks quota usage.

Script: python scripts/indexing_notify.py --batch <file> --json

GA4 Traffic

All GA4 reports accept an optional --page <path-or-url> flag to scope the report to a single landing page (EXACT match against GA4's landingPage dimension; full URLs are auto-stripped to path). Use it whenever the question is "how is this post performing?" rather than site-wide.

--report organic and --report top-pages accept --channel <name|all>: defaults to organic (Organic Search), pass all to drop the channel filter (required for whole-page weekly trends across all traffic sources), or any GA4 default channel group verbatim — Direct, Referral, Paid Search, Organic Social, etc.

ga4 [property-id]

Daily-time-series traffic report: sessions, users, pageviews, bounce rate, engagement.

Script: python scripts/ga4_report.py --property <id> --json Reference: references/ga4-data-api.md Default: 28 days, filtered to Organic Search channel group. Pass --channel all for unfiltered traffic.

The all-channels variant is what answers "how is this post growing week over week?" when most of the traffic is Direct or Referral rather than Organic — the canonical case for AI-cited content. Example: --report organic --page /blog/best-ai-seo-tools/ --channel all --days 99.

ga4-pages [property-id]

Top landing pages ranked by sessions for the chosen channel (default Organic Search; use --channel all for site-wide top pages across every source).

Script: python scripts/ga4_report.py --property <id> --report top-pages --json

ga4-referrals [property-id]

Referral sessions broken down by sessionSource. Defaults to a curated AI-assistant hostname list — OpenAI (chatgpt.com, chat.openai.com), Anthropic (claude.ai), Google (gemini.google.com, bard.google.com), Microsoft (copilot.microsoft.com), Perplexity (perplexity.ai), Alibaba/Qwen (chat.qwen.ai, qwen.com, tongyi.aliyun.com), Mistral (chat.mistral.ai), DeepSeek (chat.deepseek.com), xAI/Grok (grok.com, x.ai), plus you.com / phind.com / poe.com — so the "how much traffic do AI assistants actually send us?" question is one command. Use this as a reality check against AI-visibility data from seo-ai-search-share-of-voice and seo-geo — referral volume measures users sharing your links in AI chats, not whether the AI proactively cites you.

Script: python scripts/ga4_report.py --property <id> --report referrals --json

Source modes (--sources):

• ai (default) — curated AI-assistant hostname list
• all — every source in the Referral channel group
• chatgpt.com,perplexity.ai,... — explicit comma-separated list

Combine with --page to answer "how much AI traffic did THIS specific post get?": --report referrals --page /blog/best-ai-seo-tools/.

ga4-channel-mix [property-id]

Sessions broken down by sessionDefaultChannelGroup (Direct / Organic Search / Referral / Paid Search / Organic Social / …). No channel filter — this is the diagnostic view for "where does traffic to this page actually come from?". Each row includes a share_of_sessions percentage so the mix is visible at a glance.

Script: python scripts/ga4_report.py --property <id> --report channel-mix --json

This is the report that answers questions like "is this post mostly winning on organic, or is the traffic coming from somewhere else?". AI-assistant traffic frequently lands in Direct (uncredited) rather than Referral, so a high Direct share on a recent content-heavy page is itself an AI-visibility signal — pair with ga4-referrals for a fuller picture.

Per-page diagnosis: --report channel-mix --page /blog/best-ai-seo-tools/ --days 90.

ga4-properties

Enumerates every GA4 account and property the service account can read. Use this before running ga4 / ga4-pages / ga4-referrals / ga4-channel-mix when the client has multiple GA4 properties (typical: separate marketing-site and app properties, or per-region properties) and you need to know which property_id to query. Output groups properties by parent account; the property_id field is the numeric value to pass as --property.

Script: python scripts/ga4_admin.py properties --json

Requires the Google Analytics Admin API to be enabled in your Cloud project (separate from the Data API) and the service account to have Viewer access on at least one property.

YouTube (Video SEO)

YouTube mentions have the strongest AI visibility correlation (0.737). Free, API key only.

youtube <query>

Search YouTube for videos. Returns title, channel, views, likes, duration.

Script: python scripts/youtube_search.py search "<query>" --json Reference: references/youtube-api.md Quota: 100 units per search (10,000 units/day free).

youtube-video <video_id>

Detailed video info + tags + top 10 comments.

Script: python scripts/youtube_search.py video <video_id> --json Quota: 2 units (video details + comments).

NLP Content Analysis

Google's own entity/sentiment analysis. Enhances E-E-A-T scoring.

nlp <url-or-text>

Full NLP analysis: entities, sentiment, content classification.

Script: python scripts/nlp_analyze.py --url <url> --json or --text "..." Reference: references/nlp-api.md Free tier: 5,000 units/month. Requires billing enabled on GCP project.

entities <url-or-text>

Entity extraction only (faster, less quota).

Script: python scripts/nlp_analyze.py --url <url> --features entities --json

Keyword Research (Google Ads)

Gold-standard keyword volume data. Requires Google Ads account.

keywords <seed>

Generate keyword ideas from seed terms.

Script: python scripts/keyword_planner.py ideas "<seed>" --json Reference: references/keyword-planner-api.md Requires: Ads developer token + customer ID in config (Tier 3).

volume <keywords>

Search volume for specific keywords (comma-separated).

Script: python scripts/keyword_planner.py volume "<kw1>,<kw2>" --json

Supplementary

entity <query>

Knowledge Graph entity check. Verifies brand presence.

Reference: references/supplementary-apis.md Uses Knowledge Graph Search API with API key.

safety <url>

Web Risk API check for malware/social engineering flags.

Reference: references/supplementary-apis.md

quotas

Display rate limits table. Read references/rate-limits-quotas.md.

Reports

After any analysis command, offer to generate a PDF/HTML/XLSX report.

report <type>

Generate a professional PDF/HTML/XLSX report with charts and analytics.

Script: python scripts/google_report.py --type <type> --data <json> --domain <domain> --format pdf

Workflow:

1. Run data collection commands (pagespeed, gsc, inspect-batch, etc.)
2. Save JSON output to file: python scripts/pagespeed_check.py <url> --json > data.json
3. Generate report: python scripts/google_report.py --type cwv-audit --data data.json --domain <domain>

Convention: After completing analysis, suggest: "Generate a report? Use report <type>."

Rate Limits

Cross-Skill Integration

• seo-technical-audit — uses pagespeed_check.py for real CWV field data; uses inspect to confirm indexation status flagged by SE Ranking's audit.
• seo-page — replaces estimated traffic with real GSC query,page data via gsc; confirms indexation via inspect.
• seo-drift — adds crux-history (25-week trend) and GSC delta tracking to baseline/compare snapshots.
• seo-sitemap — sitemaps command shows which sitemaps Google has actually consumed and their error/warning counts (vs SE Ranking's audit which only crawls).
• seo-content-audit — nlp enhances E-E-A-T entity/sentiment scoring on the page being audited; gsc confirms whether the page is earning impressions for its target keywords.
• seo-geo — gsc --ai-overview --page <url> answers "did this URL appear in AI Overview, and what did it earn?" with Google's own data, complementing the SE Ranking AIO citation pull. Pair gsc --ai-overview --dimensions query,page with the GEO recommendations to confirm wins/losses URL-by-URL.
• seo-ai-search-share-of-voice — pair ga4-referrals (downstream traffic from chatgpt.com/perplexity.ai/gemini.google.com etc.) with the SoV pull (upstream citation/brand mention presence) for a complete AI-visibility picture: SoV measures whether LLMs cite you, GA4 referrals measure whether their users actually click through.
• seo-keyword-cluster / seo-keyword-niche — volume (Tier 3) replaces SE Ranking volume with Google Ads gold-standard volumes when available.
• seo-plan — when GSC + GA4 are configured, the "Where you are" baseline uses real impressions/clicks/conversions instead of SE Ranking estimates.

Output Format

• CWV metrics: traffic-light rating (Good / Needs Improvement / Poor)
• Performance reports: tables with sortable columns
• Always include data freshness note
• Save reports as GOOGLE-API-REPORT-{domain}.md
• Use templates from assets/templates/ for structured output

Technical Notes

• INP replaced FID on March 12, 2024. Never reference FID.
• CLS values from CrUX are string-encoded (e.g., "0.05"). Scripts handle parsing.
• CrUX 404 = insufficient traffic, not an auth error.
• Search Analytics data has a 2-3 day lag.
• round_trip_time replaced effectiveConnectionType in CrUX (Feb 2025).
• Custom Search JSON API is closed to new customers (2025).

Error Handling