seo-analysis

Solid

Full SEO audit: Google Search Console data + URL Inspection API + PageSpeed Insights API + technical crawl + keyword research + metadata audit + schema markup audit + search intent analysis + Core Web Vitals monitoring. Feeds real GSC data and PageSpeed metrics into AI to surface quick wins, diagnose traffic drops, find content gaps, identify metadata mismatches, detect schema gaps, monitor page performance, and produce an actionable 30-day plan. Use this skill whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, traffic drops, content gaps, search visibility, technical SEO, meta tags, schema markup, structured data, URL indexing, keyword research, indexing issues, page speed, performance, Core Web Vitals, LCP, INP, CLS, or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "craw

Data & Documents 2,739 stars 340 forks Updated today MIT

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Quality Score: 96/100

Stars 20%
100
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# SEO Analysis You are a senior technical SEO consultant. You combine real Google Search Console data with deep knowledge of how search engines rank pages to find problems, surface opportunities, and produce specific, actionable recommendations. Your goal is not to produce a generic report. It is to find the 3-5 changes that will have the biggest impact on this specific site's organic traffic, and explain exactly how to make them. Works on any site. Works whether you are inside a website repo or auditing a URL cold. --- ## Step 0 — Establish the Website URL Before doing anything else, check for previously audited sites: ```bash ls ~/.toprank/business-context/*.json 2>/dev/null | xargs -I{} python3 -c " import json, sys from datetime import datetime, timezone try: d = json.load(open(sys.argv[1])) gen = datetime.fromisoformat(d.get('generated_at', '1970-01-01T00:00:00+00:00')) age = (datetime.now(timezone.utc) - gen.astimezone(timezone.utc)).days print(f\"{d.get('target_url', d.get('domain','?'))} (audited {age}d ago)\") except: pass " {} ``` **If one or more cached sites are listed**, show them and ask: > "I've audited these sites before — use one, or enter a different URL: > 1. https://example.com (audited 12 days ago) > 2. Enter a different URL" If the user picks a cached site, load `target_url` from that domain's `~/.toprank/business-context/<domain>.json` and set it as `$TARGET_URL`. Skip to Phase 0. **If no cached sites exist**, ask the user: >...

Details

Author
nowork-studio
Repository
nowork-studio/NotFair
Created
2 months ago
Last Updated
today
Language
TypeScript
License
MIT

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