seo-geo-sources

name	seo-geo-sources
description	SEO blog research workstation. Automates pre-writing source collection - AI visibility audits, competitor article analysis, user question mining, expert quote gathering, social media trend scanning, and data/statistics harvesting. Outputs structured Blog Writing Resources to Google Sheets.

SEO/GEO Blog Sources Collector

The research phase of blog production. Before writing any SEO/GEO article, this skill systematically collects all the raw materials: competitive intelligence, user questions, expert quotes, hard data, social proof, and trend signals. Outputs everything to a structured Google Sheets template ready for the writing phase.

When to Use

• "Research sources for a blog about [keyword]"
• "Prepare blog writing resources for [topic]"
• "Do a competitive analysis for [keyword] before I write"
• "Find data, quotes, and user questions about [topic]"

Required Context (ask if not provided)

• Primary keyword(s): The target search query
• Blog title (if decided): Or the skill helps refine it
• Target audience: Who is this article for?
• Output sheet: Existing Blog Writing Resources sheet, or create new

Platform Integrations

Platform	Usage
Google Search	SERP analysis, competitor articles, PAA questions
ChatGPT (Browser)	AI visibility check - what does ChatGPT cite?
Perplexity (Browser)	AI visibility check - what does Perplexity cite?
AnswerSocrates	User question mining
Twitter/X (Browser)	Viral content, expert opinions, trend signals
Reddit (Browser)	User pain points, authentic discussions
YouTube (Browser)	Video content trends, title format research
LinkedIn (Browser)	Expert quotes, industry insights
Google Sheets	Output: Blog Writing Resources template
Google Docs (optional)	Full research brief export

Default Output Sheet

Spreadsheet ID: 1imXTbVhmDlg23ao9695Py1RZYnWxH3qyAiquSxvflxo

Safety Rules

• Read-only on all platforms - no posting, commenting, or engaging
• Wait 5-8 seconds between page loads on social platforms
• Maximum 20 Google searches per session
• Maximum 10 social media searches per platform per session
• Respect robots.txt - don't scrape blocked pages

Research Pipeline (6 Modules)

Module 1: AI Visibility Audit

Check if the topic/brand is cited by AI engines:

// 1a. ChatGPT
var page = await browser.newtab("https://chatgpt.com")
await page.wait({ waitTime: 3 })
// Ask: "What are the best [keyword] tools/solutions in 2026?"
// Record: which products/brands are cited, verbatim

// 1b. Perplexity
await page.goto({ url: "https://perplexity.ai" })
// Ask same query, record citations with source URLs

// 1c. Google AI Overview
// Search keyword on Google, check AI Overview panel
// Record what's featured

Output fields:

• AI engines checked (ChatGPT, Perplexity, Google AI)
• Products/brands cited by each
• Is Sai/Simular mentioned? (Y/N)
• Citation gap analysis (what Sai does that nobody mentions)

Module 2: User Question Mining

Collect real questions people ask about this topic:

// 2a. AnswerSocrates
await page.goto({ url: "https://answersocrates.com/" })
// Enter keyword, collect question clusters
// Target: 15-20 questions organized by type (what, how, why, which, can)

// 2b. Google PAA (People Also Ask)
// From SERP, expand PAA boxes
// Collect 8-10 additional questions

// 2c. Reddit search
await page.goto({ url: "https://www.reddit.com/search/?q=" + encodeURIComponent(keyword) + "&sort=relevance&t=year" })
// Find top 5 discussion threads
// Extract actual user questions and pain points from comments

Output fields:

• 15-20 user questions (become H2 heading candidates)
• Pain points from Reddit (authentic user frustrations)
• Question categories (definition, comparison, how-to, troubleshooting)

Module 3: Competitor Article Analysis

Deep-dive top SERP results:

// Search Google for the keyword
// Open top 5 organic results
for (var i = 0; i < 5; i++) {
  // For each competitor article, extract:
  var analysis = {
    url: "...",
    title: "...",
    wordCount: 0,       // estimate from page length
    h2Headings: [],     // all section headings
    toolsCovered: [],   // which products they review
    hasComparisonTable: false,
    hasFAQ: false,
    hasMethodology: false,
    uniqueAngles: [],   // what makes this article different
    weaknesses: []      // what's missing that we can cover
  }
}

Output fields:

• Top 5 competitor URLs with titles
• Common H2 patterns across competitors
• Tools/products every competitor mentions
• Content gaps (what nobody covers - our opportunity)
• Format analysis (table? FAQ? video embed? word count?)

Module 4: Data & Statistics Harvesting

Find hard numbers to cite in the article:

// Search for industry reports and statistics
var dataQueries = [
  keyword + " statistics 2025 2026",
  keyword + " market size report",
  keyword + " survey results",
  keyword + " benchmark data"
]
// For each query, find 3-5 citable data points
// Record: the statistic, the source, the year, the URL

Output fields:

• 8-12 citable statistics with sources
• Market size / growth data
• User adoption / usage numbers
• ROI / efficiency improvement data
• Source credibility rating (Gartner/Forrester = high, blog = low)

Module 5: Expert Quote Collection

Find quotable opinions from industry experts:

// 5a. Twitter/X search for expert opinions
await page.goto({ url: "https://x.com/search?q=" + encodeURIComponent(keyword) + "&f=top" })
// Find tweets from verified/high-follower accounts
// Record: name, credentials, quote, engagement metrics

// 5b. LinkedIn search for thought leaders
await page.goto({ url: "https://www.linkedin.com/search/results/content/?keywords=" + encodeURIComponent(keyword) })
// Find posts from industry leaders
// Record: name, title, company, key insight

Output fields:

• 5-8 expert quotes with full attribution
• Expert name, title, company, credentials
• The quote (verbatim or paraphrased)
• Source link (tweet/post URL)

Module 6: Social Media Trend Scan

Identify viral content and trending angles:

// 6a. Twitter/X - viral posts (past 3 months)
// Search keyword + variations, sort by engagement
// Record: hook formula, engagement metrics, content angle

// 6b. YouTube - top videos
await page.goto({ url: "https://www.youtube.com/results?search_query=" + encodeURIComponent(keyword) + "&sp=CAMSAhAB" })
// Sort by view count, analyze top 5 video titles
// Record: title format, view count, publish date

// 6c. Reddit - trending discussions
// Find most upvoted threads in past 3 months
// Record: topic angle, sentiment, common complaints

Output fields:

• Top 5 viral social posts with engagement data
• Viral hook formulas that worked
• Trending content angles
• Audience sentiment summary
• YouTube title patterns that get views

Output Format

Google Sheets Structure

Row for each keyword researched:
Column A: Target Audience / Segment
Column B: Primary Keywords
Column C: AI Visibility Report
Column D: User Questions (AnswerSocrates + PAA + Reddit)
Column E: SERP Intent Classification
Column F: Top Competitor Articles (URLs + analysis)
Column G: Statistics & Data Points
Column H: Expert Quotes
Column I: Social Media Trends
Column J: Recommended Blog Title
Column K: Recommended H2 Structure
Column L: Content Gaps (our unique angle)

Optional: Research Brief (Google Doc)

For complex articles, export a full research brief document:

var brief = await google.docs.createDocument({
  title: "Research Brief: " + keyword + " - " + new Date().toISOString().slice(0,10)
})
// Insert all 6 modules' findings in a structured document

Quality Checks

Before marking research complete:

• AI visibility checked on 3+ engines
• 15+ user questions collected
• 5+ competitor articles analyzed
• 8+ data points with sources
• 5+ expert quotes with attribution
• Social trends from 3+ platforms
• Content gaps identified (unique angle for our article)
• All data recorded in the output sheet