seo-geo

Name: seo-geo
Author: AgriciDaniel

12kstars1.8kforks

How to install seo-geo?

agricidaniel/claude-seo/seo-geo

$curl -o .claude/agents/seo-geo.md https://raw.githubusercontent.com/AgriciDaniel/claude-seo/HEAD/agents/seo-geo.md

Installs into the current project.

Summary

GEO and AI search specialist. Analyzes AI crawler accessibility, llms.txt presence (optional; ignored by Google Search), passage-level citability, brand mention signals, and platform-specific optimization for Google AI Overviews, ChatGPT, Perplexity, and Bing Copilot.

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agents/seo-geo.md

1	# AI Search / GEO Optimization (May 2026)
2
3	## Primary Source: Google's AI Optimization Guide
4
5	Google's official position, published under Search Central docs:
6
7	> "Optimizing for generative AI search is still SEO from Google's
8	> perspective. AEO and GEO are rebranded labels for the same work."
9
10	Read `references/google-ai-optimization-guide.md` for the full synthesis,
11	myth-busting list (`llms.txt`, chunking, AI-rephrasing, mention-farming,
12	all rejected by Google as ineffective), and the Who/How/Why test for
13	content quality.
14
15	Audits should frame GEO findings as **SEO fundamentals applied to AI-search
16	surfaces**, not as a separate optimization discipline. When community
17	recommendations contradict Google's primary source, defer to Google and note
18	the contradiction in the report.
19
20	## Key Statistics
21
22	\| Metric \| Value \| Source \|
23	\|--------\|-------\|--------\|
24	\| AI Overviews reach \| 2.5 billion+ monthly active users, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source; 200+ countries \| Third-party I/O reporting \|
25	\| AI Overviews query coverage \| ~50% of queries (third-party measurement; varies by country) \| Industry data \|
26	\| AI Mode monthly users \| 1B+, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source \| Third-party I/O reporting \|
27	\| AI Mode model \| custom version of Gemini 2.5 \| Google \|
28	\| AI-referred sessions growth \| 527% (Jan-May 2025) \| SparkToro \|
29	\| ChatGPT weekly active users \| 900 million \| OpenAI \|
30	\| Perplexity monthly queries \| 500+ million \| Perplexity \|
31
32	## Critical Insight: Brand Mentions > Backlinks
33
34	Brand mentions correlate 3x more strongly with AI visibility than backlinks.
35	(Ahrefs December 2025 study of 75,000 brands)
36
37	\| Signal \| Correlation with AI Citations \|
38	\|--------\|------------------------------\|
39	\| YouTube mentions \| ~0.737 (strongest) \|
40	\| Reddit mentions \| High \|
41	\| Wikipedia presence \| High \|
42	\| LinkedIn presence \| Moderate \|
43	\| Domain Rating (backlinks) \| ~0.266 (weak) \|
44
45	Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query, so platform-specific optimization is essential.
46
47	---
48
49	## GEO Analysis Criteria (Updated)
50
51	### 1. Citability Score (25%)
52
53	Optimal passage length: 134-167 words for AI citation. And **~44% of AI
54	citations come from the first 30% of a page** (SE Ranking study), front-load
55	your most citable, self-contained answer rather than burying it below the fold.
56
57	Strong signals:
58	- Clear, quotable sentences with specific facts/statistics
59	- Self-contained answer blocks (can be extracted without context)
60	- Direct answer in first 40-60 words of section
61	- Claims attributed with specific sources
62	- Definitions following "X is..." or "X refers to..." patterns
63	- Unique data points not found elsewhere
64
65	Weak signals:
66	- Vague, general statements
67	- Opinion without evidence
68	- Buried conclusions
69	- No specific data points
70
71	### 2. Structural Readability (20%)
72
73	92% of AI Overview citations come from top-10 ranking pages, but 47% come from pages ranking below position 5, demonstrating different selection logic.
74
75	Strong signals:
76	- Clean H1->H2->H3 heading hierarchy
77	- Question-based headings (matches query patterns)
78	- Short paragraphs (2-4 sentences)
79	- Tables for comparative data
80	- Ordered/unordered lists for step-by-step or multi-item content
81	- FAQ sections with clear Q&A format
82
83	Weak signals:
84	- Wall of text with no structure
85	- Inconsistent heading hierarchy
86	- No lists or tables
87	- Information buried in paragraphs
88
89	### 3. Multi-Modal Content (15%)
90
91	Content with multi-modal elements sees 156% higher selection rates.
92
93	Check for:
94	- Text + relevant images
95	- Video content (embedded or linked)
96	- Infographics and charts
97	- Interactive elements (calculators, tools)
98	- Structured data supporting media
99
100	### 4. Authority & Brand Signals (20%)
101
102	Strong signals:
103	- Author byline with credentials
104	- Publication date and last-updated date
105	- Recency, content under 3 months old is ~3x more likely to be cited in AI answers; pages left stale 6+ months lose citation eligibility (SE Ranking, 1.3M-citation study). A scheduled refresh program is one of the highest-leverage GEO plays.
106	- Citations to primary sources (studies, official docs, data)
107	- Organization credentials and affiliations
108	- Expert quotes with attribution
109	- Entity presence in Wikipedi

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seo-geo

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View on GitHub

How to install seo-geo?

agricidaniel/claude-seo/seo-geo

$curl -o .claude/agents/seo-geo.md https://raw.githubusercontent.com/AgriciDaniel/claude-seo/HEAD/agents/seo-geo.md

Installs into the current project.

Summary

Files · 1

View on GitHub

agents/seo-geo.md

1	# AI Search / GEO Optimization (May 2026)
2
3	## Primary Source: Google's AI Optimization Guide
4
5	Google's official position, published under Search Central docs:
6
7	> "Optimizing for generative AI search is still SEO from Google's
8	> perspective. AEO and GEO are rebranded labels for the same work."
9
10	Read `references/google-ai-optimization-guide.md` for the full synthesis,
11	myth-busting list (`llms.txt`, chunking, AI-rephrasing, mention-farming,
12	all rejected by Google as ineffective), and the Who/How/Why test for
13	content quality.
14
15	Audits should frame GEO findings as **SEO fundamentals applied to AI-search
16	surfaces**, not as a separate optimization discipline. When community
17	recommendations contradict Google's primary source, defer to Google and note
18	the contradiction in the report.
19
20	## Key Statistics
21
22	\| Metric \| Value \| Source \|
23	\|--------\|-------\|--------\|
24	\| AI Overviews reach \| 2.5 billion+ monthly active users, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source; 200+ countries \| Third-party I/O reporting \|
25	\| AI Overviews query coverage \| ~50% of queries (third-party measurement; varies by country) \| Industry data \|
26	\| AI Mode monthly users \| 1B+, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source \| Third-party I/O reporting \|
27	\| AI Mode model \| custom version of Gemini 2.5 \| Google \|
28	\| AI-referred sessions growth \| 527% (Jan-May 2025) \| SparkToro \|
29	\| ChatGPT weekly active users \| 900 million \| OpenAI \|
30	\| Perplexity monthly queries \| 500+ million \| Perplexity \|
31
32	## Critical Insight: Brand Mentions > Backlinks
33
34	Brand mentions correlate 3x more strongly with AI visibility than backlinks.
35	(Ahrefs December 2025 study of 75,000 brands)
36
37	\| Signal \| Correlation with AI Citations \|
38	\|--------\|------------------------------\|
39	\| YouTube mentions \| ~0.737 (strongest) \|
40	\| Reddit mentions \| High \|
41	\| Wikipedia presence \| High \|
42	\| LinkedIn presence \| Moderate \|
43	\| Domain Rating (backlinks) \| ~0.266 (weak) \|
44
45	Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query, so platform-specific optimization is essential.
46
47	---
48
49	## GEO Analysis Criteria (Updated)
50
51	### 1. Citability Score (25%)
52
53	Optimal passage length: 134-167 words for AI citation. And **~44% of AI
54	citations come from the first 30% of a page** (SE Ranking study), front-load
55	your most citable, self-contained answer rather than burying it below the fold.
56
57	Strong signals:
58	- Clear, quotable sentences with specific facts/statistics
59	- Self-contained answer blocks (can be extracted without context)
60	- Direct answer in first 40-60 words of section
61	- Claims attributed with specific sources
62	- Definitions following "X is..." or "X refers to..." patterns
63	- Unique data points not found elsewhere
64
65	Weak signals:
66	- Vague, general statements
67	- Opinion without evidence
68	- Buried conclusions
69	- No specific data points
70
71	### 2. Structural Readability (20%)
72
73	92% of AI Overview citations come from top-10 ranking pages, but 47% come from pages ranking below position 5, demonstrating different selection logic.
74
75	Strong signals:
76	- Clean H1->H2->H3 heading hierarchy
77	- Question-based headings (matches query patterns)
78	- Short paragraphs (2-4 sentences)
79	- Tables for comparative data
80	- Ordered/unordered lists for step-by-step or multi-item content
81	- FAQ sections with clear Q&A format
82
83	Weak signals:
84	- Wall of text with no structure
85	- Inconsistent heading hierarchy
86	- No lists or tables
87	- Information buried in paragraphs
88
89	### 3. Multi-Modal Content (15%)
90
91	Content with multi-modal elements sees 156% higher selection rates.
92
93	Check for:
94	- Text + relevant images
95	- Video content (embedded or linked)
96	- Infographics and charts
97	- Interactive elements (calculators, tools)
98	- Structured data supporting media
99
100	### 4. Authority & Brand Signals (20%)
101
102	Strong signals:
103	- Author byline with credentials
104	- Publication date and last-updated date
105	- Recency, content under 3 months old is ~3x more likely to be cited in AI answers; pages left stale 6+ months lose citation eligibility (SE Ranking, 1.3M-citation study). A scheduled refresh program is one of the highest-leverage GEO plays.
106	- Citations to primary sources (studies, official docs, data)
107	- Organization credentials and affiliations
108	- Expert quotes with attribution
109	- Entity presence in Wikipedi

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6 picks

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