Semantic SEO Prompts Library: ChatGPT, Claude, Gemini

01

Chapter 1 — Semantic Search Evolution

Semantic Search Foundations

Entity-based SEO concepts, knowledge graph terminology, query semantics — master the vocabulary and theory that underpins everything else.

🧠

P1.1 — Entity Relationship & Knowledge Graph Analysis

Understand entity triples, salience, disambiguation for any topic

ChatGPTClaudeGeminiBeginner

▸ Full Prompt — Copy & Paste

You are a Semantic SEO expert trained in entity-based SEO and Google's Knowledge Graph architecture. My topic / niche: [YOUR TOPIC — e.g., "Coffee Brewing Methods"] My central entity: [YOUR ENTITY — e.g., "Pour Over Coffee"] TASK 1 — ENTITY TAXONOMY Map the complete entity hierarchy: - Parent entity (what broader category does this belong to?) - The entity itself (precise definition as Google would store it) - Child entities (subcategories or types) - Sibling entities (alternatives at the same level) TASK 2 — ENTITY ATTRIBUTES List all attributes Google would store for this entity: | Attribute Name | Data Type | Example Value | SEO Importance (High/Med/Low) | TASK 3 — ENTITY TRIPLES (S–P–O) Generate 15 factual Subject→Predicate→Object triples about this entity. These triples should be facts I must cover in my content. | Subject | Predicate (verb) | Object | Why Google needs this | TASK 4 — ENTITY DISAMBIGUATION Are there any disambiguation issues with this entity name? If yes: What contextual signals should I use to clarify which entity I mean? TASK 5 — ENTITY SALIENCE SIGNALS How should I write my content so this entity has HIGH salience? Give 5 specific writing instructions for maximum entity salience.

▸ Real Example Output (Coffee Niche)

Example — Central Entity: "Pour Over Coffee" Parent: Coffee Brewing Methods → Pour Over Coffee → [V60, Chemex, Kalita Wave]
Sibling entities: French Press, AeroPress, Cold Brew, Espresso

Sample Triple: "Pour Over Coffee" → requires → "Gooseneck Kettle" (attribute: equipment)
Sample Triple: "Pour Over Coffee" → produces → "Clean, Bright Flavor Profile" (attribute: taste)
Sample Triple: "Pour Over Coffee" → uses → "Medium-Fine Grind" (attribute: grind size)

Disambiguation: "Pour Over" could mean paint/coating — add context: "Pour Over Coffee brewing method" in H1 and first paragraph.

💡 When to use: Run this before creating any page. The triples you generate become the mandatory facts your content must cover. Missing these = missing entity completeness signals Google needs to rank you.

🔍

P1.2 — Query Semantics & Search Intent Deep Analysis

Decode how Google classifies queries — sub-intents, query rewriting, contextual search

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a search intent analyst trained in Google's query classification systems. Target query: [YOUR QUERY — e.g., "best pour over coffee maker"] My website niche: [YOUR NICHE] TASK 1 — INTENT CLASSIFICATION Classify this query: - Primary intent type: Informational / Commercial / Transactional / Navigational - Sub-intent types: List all secondary intents within this query - Query class: What "job" is the user hiring this search to do? - Urgency level: How immediately does the user need a solution? TASK 2 — QUERY REWRITING SIMULATION How would Google rewrite or expand this query internally? List 5 rewritten versions Google might process this query as. TASK 3 — SUB-INTENT EXPANSION What deeper sub-intents exist within this query? For each sub-intent: what does the user actually want to know/do/buy? | Sub-Intent | What User Wants | Content Format to Address It | TASK 4 — QUERY NETWORK MAPPING Map the query network around this query: - Query Path: 3 queries users search BEFORE this query - Correlated Queries: 5 queries searched in the same session - Sequential Queries: 3 queries users search AFTER this query TASK 5 — CONTENT RECOMMENDATION Based on this intent analysis, what EXACT content structure should I create? Recommend: page type, word count range, content format, 5 H2 headings.

Example — Query: "best pour over coffee maker" Primary Intent: Commercial Investigation (comparing before buying)
Sub-intents: [Which brand is best?] [What features matter?] [Price comparison] [Beginner vs. expert options]
Google Rewrite: "top rated pour over coffee drippers 2024" / "pour over coffee maker comparison guide"
Query Path: "what is pour over coffee" → "how to make pour over coffee" → "best pour over coffee maker"
Sequential: "V60 vs Chemex" → "where to buy Hario V60" → "pour over coffee beans"

02

Chapter 2 — Steps 1–19 | Topical Map Creation

Topical Map — Full Creation System

Source context, central entity selection, core/outer topics, Frame Semantics, audience personas, entity discovery, SERP research, and final map output.

🗺️

P2.1 — Source Context + Central Entity Selection (Steps 1–2)

Define ultimate offer, root entity, and full ontology

ChatGPTClaudeGeminiStart Here

▸ Full Prompt — Copy & Paste

You are a Semantic SEO strategist trained in Koray Tugberk GUBUR's topical map creation system. I am building a topical map from scratch. MY BUSINESS DETAILS Business name: [YOUR BUSINESS NAME] Niche / industry: [YOUR NICHE — e.g., "Specialty Coffee Equipment"] Main product/service: [WHAT YOU SELL — e.g., "Pour Over Coffee Makers, Grinders, Kettles"] Ultimate monetary offer: [HOW YOU MAKE MONEY — e.g., "Affiliate commissions from Amazon + own coffee gear store"] Ultimate non-monetary offer: [FREE VALUE YOU PROVIDE — e.g., "Brewing guides, recipes, equipment reviews"] Target audience: [WHO — e.g., "Home coffee enthusiasts who want cafe-quality coffee"] Target region/language: [e.g., "United States, English"] STEP 1 — SOURCE CONTEXT ANALYSIS Analyze my source context and define: 1. My core problem I am solving for the audience 2. The business model and how content supports it 3. The transformation my audience seeks (from → to) STEP 2 — CENTRAL ENTITY IDENTIFICATION Let's think step by step. Identify the single best central/root entity for my website: - Name the entity - Explain WHY this entity (not another) is the correct root - Is it specific enough to build authority, broad enough to cover the niche? STEP 2.1 — ONTOLOGY OF THE CENTRAL ENTITY Develop the complete ontology for this central entity: Parent concepts: [2–3 broader categories above this entity] The entity: [definition as Google stores it] Child entities: [6–8 subcategories or types] Sibling entities: [5–6 competing/alternative entities at the same level] Key attribute classes: [5–6 main property types] Key relationship types: [4–5 how this entity relates to others]

Example — Specialty Coffee Equipment Niche Central Entity: "Pour Over Coffee" (specific enough to build authority, broad enough to cover equipment + technique + beans)
Parent: Coffee → Manual Coffee Brewing → Pour Over Coffee
Children: V60, Chemex, Kalita Wave, Origami Dripper, Bee House
Siblings: French Press, AeroPress, Moka Pot, Cold Brew, Siphon

💡 Key Rule: The central entity must be specific enough to build deep authority but broad enough to justify 50–200 pages of content. "Coffee" is too broad. "V60 Coffee" is too narrow. "Pour Over Coffee" is ideal.

🏛️

P2.2 — Core + Outer Sections + Frame Semantics (Steps 3–6)

Define content pillars, search intent, peripheral topics, and semantic frames

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Semantic SEO topical map architect. I need to define the complete topic architecture for my website. Central Entity (from Step 2): [e.g., "Pour Over Coffee"] Niche: [e.g., "Specialty Coffee Equipment & Brewing"] Business Type: [B2B / B2C / Local / Ecommerce / Blog] Audience: [e.g., "Home coffee enthusiasts, skill level: beginner to intermediate"] STEP 3 — CORE SECTION TOPICS Identify 6–10 PRIMARY content pillars for the core section. For each core topic: - Topic name - Why it's core (relation to central entity) - Primary search intent (Info/Commercial/Trans/Nav) - Estimated page count needed (1–10) - Priority: High / Medium STEP 4 — CENTRAL SEARCH INTENT What is the holistic search intent of my entire website? What 3 macro questions does my entire website exist to answer? STEP 4.1 — FRAME SEMANTICS ANALYSIS Identify 5–7 "frames" — scenarios or situations that motivate searches in my niche. For each frame: - Frame name - The situation / context the user is in - The roles involved - The goal the user wants to achieve - 3 example queries this frame produces STEP 6 — OUTER SECTION TOPICS Identify 8–12 PERIPHERAL topics that relate to but don't define my core niche. For each outer topic: - Topic name | How it connects | Why it's outer | Search volume tier: High / Medium / Low

Example — Core Topics for "Pour Over Coffee" niche Core Pillars: [1] Pour Over Equipment Reviews [2] Brewing Techniques & Ratios [3] Coffee Bean Selection [4] Grinders for Pour Over [5] Water Temperature & Quality [6] Troubleshooting (bitter/weak coffee)

Frame Example: "Gift Giver Frame" — Situation: Person wants to buy coffee gear as a gift. Queries: "best pour over coffee gift set", "pour over coffee starter kit under $50"

👥

P2.3 — Audience Personas + Authority Source Selection (Steps 7–9)

Buyer personas, knowledge domain terms, reverse-engineer competitor

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Semantic SEO audience and authority analyst. Niche: [e.g., "Pour Over Coffee Equipment & Brewing"] Central entity: [e.g., "Pour Over Coffee"] My 3–5 main competitors: [LIST COMPETITOR WEBSITES] STEP 7 — BUYER PERSONAS Create 3 detailed buyer personas for my audience. For each persona: - Persona name + demographics - Knowledge level (beginner/intermediate/expert) - Primary goals + pain points - How they search (query patterns, question types) - Vocabulary they use (domain terms they know vs. don't know) - Content format they prefer (step-by-step, comparison, video-style) - Trust signals they look for STEP 7 TOOL — KNOWLEDGE DOMAIN TERMS For each persona, extract: - 10 domain terms they use when searching - 5 questions they commonly ask in forums/Reddit/Quora - 3 misconceptions they often have about my niche - Vocabulary I should use vs. avoid STEP 8 — AUTHORITY SOURCE IDENTIFICATION From my listed competitors, evaluate each: | Competitor | Estimated Topic Coverage | DA/DR Level | Traffic-to-Pages Ratio | Backlink Dependency | STEP 9 — SELECT THE AUTHORITY SOURCE TO REVERSE-ENGINEER Select the ONE best authority source to benchmark against. Ideal criteria: lower DA/DR, higher traffic-to-pages ratio, lower backlink dependency, overlapping topical coverage. Explain your selection. Then list the TOP 20 topics I should cover based on their architecture.

Example — Coffee Buyer Personas Persona 1: "Weekend Brewer Sarah" — Beginner, wants cafe-quality coffee at home. Misconception: Thinks expensive beans = good coffee automatically.
Persona 2: "Coffee Geek Marcus" — Advanced, researches gear deeply. Uses terms: "TDS measurement", "bloom phase". Trusts third-party lab testing data.

🔎

P2.4 — Derived & Related Entity Discovery (Step 10)

Cross-LLM entity research — run on ChatGPT, Claude, AND Gemini for maximum coverage

ChatGPTClaudeGeminiRun on All 3

▸ Full Prompt — Copy & Paste (Run on ALL 3 AIs for best results)

You are an NLP and entity extraction specialist for Semantic SEO. Central Entity: [e.g., "Pour Over Coffee"] Niche: [e.g., "Coffee Equipment & Brewing"] Core topics already identified: [LIST YOUR CORE TOPICS FROM P2.2] DERIVED ENTITIES (5 categories) 1. OUTCOME entities — what does the central entity PRODUCE? 2. PROCESS entities — what PROCESSES define it? 3. EQUIPMENT entities — what TOOLS are used? 4. MEASUREMENT entities — how is it EVALUATED? 5. PROBLEM entities — what PROBLEMS does it solve or create? For each entity found: name | type | relationship label | content priority (1–10) RELATED ENTITIES (5 types) 1. CO-OCCURRING: always mentioned alongside the central entity 2. PREREQUISITE: needed before using/understanding it 3. SUCCESSOR: what comes after (next steps in the user journey) 4. COMPETING: alternatives to the central entity 5. COMPLEMENTARY: used alongside it ENTITY SEMANTIC NETWORK Show the top 15 entities in a simple text network. Use arrows: Entity A →[relationship]→ Entity B Example: "Bloom" →[is part of]→ "Pour Over Technique" // Run this same prompt on ChatGPT, Claude, AND Gemini. Merge all 3 outputs to get the most complete entity list.

💡 Pro Tip: Run this on all 3 AI platforms. ChatGPT may find equipment entities Claude misses. Gemini may find scientific measurement entities. Merge all outputs — exactly what Step 10.3 of the Topical Map system recommends.

📊

P2.5 — SERP Signal Extraction + Query Template Mapping (Steps 10.2, 11)

PAA questions, autocomplete, query network, template patterns

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a SERP data analyst for Semantic SEO. Extract all query signals for my topical map. Central Entity: [e.g., "Pour Over Coffee"] Specific Topic to Analyze: [e.g., "Hario V60"] Target Audience Region: [e.g., "US"] QUERY TEMPLATES — All Patterns Generate every query template that applies to this topic: - [What is / What are / What does] + entity - [How to / How do I / How does] + action + entity - [Best / Top / Recommended] + entity + [for use case] - [Entity] vs [competitor] - [Entity] + [review / worth it / good or bad] - [Problem] + with + entity - [Entity] + [guide / tutorial / explained] - [Buy / where to buy / price of] + entity PAA QUESTIONS — 25 Questions Generate 25 People Also Ask style questions Google would show for this topic. Format: Question | Intent | Answer Format | Priority (1–10) AUTOCOMPLETE SIMULATION Complete these with 8 suggestions each: "[entity] ..." "how to use [entity] ..." "[entity] vs ..." "[entity] [problem] ..." QUERY NETWORK Query Path (before): What 4 queries lead a user TO this topic? Correlated Queries: 6 queries searched IN THE SAME SESSION Sequential Queries: 4 queries searched AFTER this topic

🧩

P2.6 — Complete Topical Map Generator (Steps 15–19)

Final production-ready topical map with clusters, hierarchy, internal linking, and calendar

ChatGPTClaudeGeminiMaster Output

▸ Full Prompt — Copy & Paste

You are a senior Semantic SEO strategist. Generate a complete, production-ready topical map. INPUT DATA Website niche: [e.g., "Pour Over Coffee Equipment & Brewing Methods"] Central entity: [e.g., "Pour Over Coffee"] Business type: [B2B/B2C/Local/Ecommerce/Blog] Target region: [e.g., "US English"] Core topics (from P2.2): [PASTE YOUR LIST] Outer topics (from P2.2): [PASTE YOUR LIST] All entities discovered (from P2.4): [PASTE YOUR LIST] Authority source to beat: [COMPETITOR URL] STEP 15 — QUERY CLUSTERING Group queries into clusters based on same SERP page. Each cluster = one future page on my website. STEPS 16–19 — COMPLETE TOPICAL MAP Generate the full map in this exact table structure: ━━━━━━━━━━━━━━━━━━━━━━━━━━ TOPICAL MAP: [NICHE NAME] Central Entity: [ENTITY] | Authority Target: [COMPETITOR] ━━━━━━━━━━━━━━━━━━━━━━━━━━ CORE SECTION — Cluster 1: [Cluster Name] | ID | Proposed H1 | Target Query | Intent | Page Type | Priority | Word Count | Links To | Repeat for all core clusters (aim for 4–6 clusters) SUPPORTING SECTION — [same table format] OUTER SECTION — [same table format] INTERNAL LINKING ARCHITECTURE Show the hub-and-spoke model: Pillar Page → [list of spoke pages linking to/from it] — for 3 main clusters. TOPICAL BORDERS List 10 topics OUTSIDE my niche that I must NOT cover. Explain why each would dilute topical authority. 3-MONTH PUBLISHING CALENDAR Month 1 (Foundation): Which 8 pages to publish first and why Month 2 (Depth): Which 8 pages to publish next Month 3 (Breadth): Which 8 pages to expand with

04

Chapter 4 — 9-Step Brief Creation System

Semantic Content Brief System

SERP analysis, contextual vectors, heading hierarchy, question mapping, entity requirements, contextual bridges — complete content brief for every page.

📋

P4.1 — SERP Competitor Analysis Brief (Steps 1–5)

Macro context, information gaps, heading vectors, authority source selection

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Semantic SEO content brief analyst. Analyze SERP competitors before I write content. Target query: [e.g., "how to make pour over coffee"] My niche: [e.g., "Pour Over Coffee Brewing"] My central entity: [e.g., "Pour Over Coffee"] Page objective: [Rank / Monetize / Both] COMPETITOR DATA (I have read these manually): Competitor 1 title + H2 structure: [PASTE TITLE + ALL HEADINGS] Competitor 2 title + H2 structure: [PASTE TITLE + ALL HEADINGS] Competitor 3 title + H2 structure: [PASTE TITLE + ALL HEADINGS] STEP 1 — MACRO CONTEXT (CONSENSUS) What is the dominant macro context shared by ALL 3 competitors? What angle/topic do all of them address? This = the consensus I must match. STEP 2 — COMPETITOR GAP ANALYSIS For EACH competitor: - What do they cover well? (their strongest sections) - What are they missing? (information gaps) - What is their unique angle? - Why does the #1 ranking page outrank the others? STEP 3 — AUTHORITY SOURCE SELECTION Evaluate each competitor: - Estimated DA/DR level (lower = better target) - Backlink dependency (how much do links carry the ranking?) - Traffic-to-page ratio (content quality signal) SELECT and justify the ONE authority source to benchmark against. STEP 4 — MACRO CONTEXT DEFINITION Define the exact macro context for MY page. Suggest a UNIQUE heading vector that matches consensus AND offers a fresh angle. STEP 5 — QUERY SEARCH DEMAND List 15 related queries I should cover in this article (sub-intents). Estimate relative volume: High / Medium / Low for each.

🏗️

P4.2 — Complete Semantic Content Brief (Steps 6–9)

Full brief: heading vectors, 20+ questions, entity list, contextual bridges, on-page checklist

ChatGPTClaudeGeminiDetailed

▸ Full Prompt — Copy & Paste

You are a Semantic SEO content brief specialist. Generate a COMPLETE content brief for a writer. Target query: [e.g., "how to make pour over coffee"] Macro context (from P4.1): [e.g., "Step-by-step brewing guide with ratios and equipment"] My unique angle (from P4.1): [e.g., "Cafe-quality pour over at home for beginners"] Target audience persona: [e.g., "Weekend Brewer Sarah — beginner, wants cafe quality"] Target word count: [e.g., "2000–2500 words"] ━━━ GENERATE COMPLETE BRIEF ━━━ 1. PAGE METADATA Title Tag (under 60 chars, include entity + attribute): Meta Description (under 155 chars, entity + benefit + CTA): H1 (different from title, includes macro context): URL slug (entity-based, no stop words): 2. CONTEXTUAL VECTOR — HEADING HIERARCHY H1: [macro context — broadest level] H2 (1): [first major subtopic — deepens H1] H3 (1a): [detail under H2.1] H3 (1b): [detail under H2.1] H2 (2): [second major subtopic] H2 (3): [third major subtopic] H2 (4): [fourth major subtopic] H2 (5): FAQ Section 3. QUESTION HIERARCHY (minimum 20 questions) Format: Question | Heading Level (H2/H3) | Answer Format | Priority (1–10) Include: informational, comparison, troubleshooting, PAA questions 4. ENTITY REQUIREMENTS Must-mention entities (with reason): Supporting entities (for context): Attribute values to specify for each entity: Entities to AVOID (outside contextual border): 5. CONTEXTUAL BRIDGES (STEP 8) - 3 pages on my site I should link TO from this page (with anchor text) - 3 pages that should link TO this page (with anchor text) - 2 transition phrases to use between sections 6. EVIDENCE & DATA REQUIREMENTS - Required data points / statistics to include - Types of evidence: research study / expert quote / user data / case study - Tables required (describe structure) 7. WRITER INSTRUCTIONS - Audience knowledge level: write for [beginner/intermediate] - Tone: [informative but conversational] - Must include: FAQ section (5 Q&As, 40 words max each)

Example — Content Brief: "How to Make Pour Over Coffee" Title: How to Make Pour Over Coffee (Step-by-Step Guide)
H1: How to Make Pour Over Coffee That Tastes Like a Cafe at Home
H2 Structure: [What You Need] → [Grind Size + Ratio] → [Step-by-Step Process] → [Common Mistakes] → [FAQ]
Must-mention entities: Gooseneck kettle, Hario V60, Bloom phase, Brew ratio (1:15), Water temp (93°C)

05

Chapter 5 — Koray's 38 Writing Rules Framework

Semantic Content Writing

Write content that Google's NLP can fully parse, extract factual triples from, and rank with high confidence. All 38 rules applied.

R01 Include entities + attribute values

R02 Single macro context per page

R03 Factual sentence structures: "X does Y"

R04 Support with research + university studies

R05 Be concise — eliminate vague superlatives

R06 Don't break context across paragraphs

R07 Optimize discourse integration

R08 Use Question + Answer format

R09 Answer immediately — never bury the answer

R10 Expand evidence with multiple examples

R11 Don't break the information graph

R12 Use shorter sentences (under 20 words)

R13 Decrease contextless words

R14 Delete all filler words

R15 Give more information per section

R16 Build proper context vector H1→H2→H3

R17 Consistent declarations across site

R18 Consistent style across documents

R19 Unique N-gram combinations

R20 Same N-grams at start and end

R21 Use only the most specific terminology

R22 Distinguish knowledge from experience

R23 Use sentence-final focus positions

R24 Precise numerical data over ranges

R25 Use taxonomic classification patterns

R26 Lead with "is" not "can be" or "may be"

R27 Process sentences before result sentences

R28 40-word featured snippet answers

R29 Use declarative language not hedging

R30 No transitional filler phrases

R31 Use exact numbers not vague quantities

R32 Establish comparative benchmarks

R33 Use active voice

R34 Always give examples for plural nouns

R35 Define every technical term first time used

R36 Attribute all claims to sources

R37 Don't start sentences with "If"

R38 Use context-rich anchor text for links

✍️

P5.1 — Semantic Content Writer (All 38 Rules Applied)

Write a complete article section applying every rule — labeled per sentence

ChatGPTClaudeGeminiAdvanced

▸ Full Prompt — Copy & Paste

You are a Semantic SEO content writer trained in Koray Tugberk GUBUR's 38 Algorithmic Authorship Rules. Write content that Google's NLP can fully parse. Topic / target query: [e.g., "how to make pour over coffee"] Central entity: [e.g., "Pour Over Coffee"] Section to write: [e.g., "H2: What grind size does pour over coffee require?"] Target audience: [e.g., "beginner home baristas"] Must-mention entities: [e.g., "burr grinder, medium-fine grind, 250–300 microns, extraction yield"] Target length: [e.g., "250–300 words"] WRITING INSTRUCTIONS Apply these rules explicitly — label each sentence [R##]: STRUCTURE RULES: [R02] One macro context: the heading defines the section topic — do not drift [R16] Context vector flows from H2 → content naturally [R08] Start section with the heading rewritten as a question [R09] Answer the question in the FIRST sentence, not at the end SENTENCE RULES: [R03] Use factual declarative statements: "X does Y" / "X is Y" [R12] Max 20 words per sentence [R26] Use "is" not "can be" / "may be" / "could be" [R29] No hedging language: no might, could, perhaps, possibly [R33] Active voice only PRECISION RULES: [R01] Include entities with their specific attribute values [R24] Use exact numbers, not ranges where possible [R31] Specific quantities: not "many" — use "4 out of 5" or "87%" [R35] Define technical terms on first use EVIDENCE RULES: [R04] Back key claims with research or expert consensus [R10] Give 2–3 concrete examples for each key point [R34] For any plural noun, give immediate examples STYLE RULES: [R05] No vague superlatives: not "important" — say WHY it matters [R13] Cut contextless words (just, really, very, basically) [R14] Delete all filler transitions (furthermore, in addition, also) [R37] Never start a sentence with "If" OUTPUT FORMAT Write the section, then provide a compliance table: | Sentence # | Rule(s) Applied | Compliance Check |

🔧

P5.2 — Content Rewriter (Fix Rule Violations)

Paste your existing content — get a full violation audit and rewrite

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Semantic SEO content editor. Audit and rewrite my content following Koray's 38 Rules. My content: [PASTE YOUR CONTENT HERE] Target query: [YOUR TARGET QUERY] Central entity: [YOUR CENTRAL ENTITY] PHASE 1 — VIOLATION AUDIT For each rule violation found, create a table: | Sentence | Rule Violated | Why It Violates | Priority (High/Med/Low) | Focus especially on these HIGH-IMPACT violations: - R08 violations: headings not in question format - R09 violations: answer buried, not in first sentence - R12 violations: sentences over 20 words - R26 violations: "can be" / "may be" instead of "is" - R29 violations: hedging language (might, perhaps, could) - R31 violations: vague quantities (many, some, several) - R37 violations: sentences starting with "If" / "When" PHASE 2 — COMPLETE REWRITE Rewrite the entire content applying all rules. After each paragraph, add: [Rules Applied: R03, R09, R12...] PHASE 3 — IMPROVEMENT SUMMARY Before vs. After comparison: - Violations removed: [number] - Entities added: [list] - Estimated readability improvement - Estimated NLP parseability improvement

🎯

P5.3 — Featured Snippet Optimization + Factual Triple Extraction

40-word answers, S-P-O triple mining, entity density analysis, QA conversion

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are an NLP and featured snippet optimization specialist. Analyze this content for Google's extraction systems. Target query: [YOUR QUERY] Content: [PASTE YOUR CONTENT] TASK 1 — FACTUAL TRIPLE EXTRACTION Extract every Subject→Predicate→Object triple in the content. | Subject | Predicate (verb) | Object | Confidence (High/Med/Low) | Type | Identify: - Strong triples: clear, factual, machine-extractable - Weak triples: vague predicate, no clear object - Missing triples: facts that SHOULD be stated but aren't TASK 2 — FEATURED SNIPPET ANSWERS (Rule 28) For each H2 heading, rewrite the opening answer to be EXACTLY 40 words or fewer. Format: Q: [Original heading as question] A: [40-word direct answer — no preamble, no hedging] TASK 3 — ENTITY DENSITY CHECK Count unique entities per 100 words in each section. Target: minimum 3 entities per 100 words. | Section | Current Entity Density | Target | Missing Entities to Add | TASK 4 — QA FORMAT CONVERSION (Rule 8) Convert every declarative H2/H3 heading to question format: | Original Heading → Question Format Version | TASK 5 — SEMANTIC RICHNESS SCORE Rate 1–10: Entity density | Factual specificity | Context vector coherence | Discourse integration | Answer immediacy Overall score: [X/50] + Top 3 priority improvements

Example — Triple Extraction for Pour Over Article "Pour Over Coffee" → requires → "Paper Filter" (High confidence, equipment-type)
"Bloom Phase" → lasts → "30–45 seconds" (High confidence, time-type)
WEAK triple found: "Good grind size is important" → Fix: "Medium-fine grind (250–300 microns) produces optimal pour over extraction"

📝

P5.4 — Complete Article Workflow (Outline/Cluster → Full Article)

Step 1 makes clear topic groups and outline. Step 2 writes full article from that approved outline.

ChatGPTClaudeGemini2-Step

▸ STEP 1 Prompt — Outline & Cluster First (Copy & Paste)

You are an SEO writer using Koray's method. Use simple English (6th grade). Do not use AI buzz words. Make the outline with Koray's 38 writing rules in mind. INPUT MODE RULE If user gives ONLY a topic name: 1) First ask for main topics (3-7) 2) Then ask missing inputs one by one 3) After user replies, continue full flow below Ask this first when data is missing: "Please share: - Main topic - Main topics list (3-7) - Reader level - User intent - Target word count" Main topic: [example: "how to make pour over coffee"] Related queries: [paste 10-20 queries] User intent: [informational / commercial] Reader level: [beginner / intermediate] Target words: [example: 2200] Main entity: [main entity] Must-use entities: [list] STEP 1 — GROUP QUERIES Group queries by one clear user need. Table: | Cluster | Queries | User Need | Priority | STEP 2 — MAKE ARTICLE OUTLINE Give: - 5 title options - 3 meta description options - 1 H1 - Full H2/H3 outline - 8 FAQ questions STEP 3 — SECTION PLAN For each H2, give: | H2 | Main question | Key entities | Word count | STEP 4 — KORAY RULE CHECK FOR OUTLINE Check outline against key rules: - One clear context per section (R02) - Headings as questions (R08) - Direct answer planned first (R09) - Clear entities and attributes (R01) - Internal link spots planned (R38) IMPORTANT: Do not write full article now. End with this line: "✅ Outline ready. Send: WRITE FULL ARTICLE"

▸ STEP 2 Prompt — Full Article from Approved Outline (Copy & Paste)

Write the full article from this approved outline: [PASTE OUTLINE FROM STEP 1] Write in simple English (6th grade). No AI buzz words. Follow Koray style and these rules: - One clear context in each section (R02) - Turn headings into real questions (R08) - Answer in first line (R09) - Short clear sentences (R12) - Use "is" statements, not weak wording (R26) - Use exact numbers when possible (R31) - Add examples after claims (R34) - Use useful internal anchors (R38) OUTPUT 1) SEO block - Final Title - Meta Description - URL Slug 2) Full article - H1, H2, H3 content - Practical examples - Simple table/list where needed - FAQ (8 questions, each answer max 40 words) 3) Final checks - Entity checklist (covered / missing) - Intent checklist (covered / missing) - Internal links to add (anchor text + target page) Target length: [example: 1800-2500 words]

💡 Best Usage Flow: First approve outline, then write full article. This keeps topic clear, covers intent better, and matches Koray's method.

❓

P5.5 — FAQ Question Generator (Layer Method + Koray Rules)

Generate high-intent FAQ questions in clear layers before writing answers

ChatGPTClaudeGeminiFAQ

▸ Full Prompt — Copy & Paste

Ask me before keyword task perform below. You are an advanced SEO strategist using Koray-style topical and intent logic. Use simple English. Do not generate generic ideas. Use layered intent logic exactly as instructed. INPUT Topic: [INSERT TOPIC] Location (optional): [City/Country or leave blank] Industry Type: [Ecommerce / Local Business / SaaS / Service / etc.] Total Questions Needed: [e.g., 100] KORAY RULES TO FOLLOW - Questions must match clear user intent - Questions must stay inside one topic context - Questions must be natural Google-style language - No vague or fluffy wording - Use specific qualifiers where needed (price, location, audience, use case) GENERATE QUESTIONS USING THESE LAYERS For the given Topic, generate question queries using ALL layers. Distribute questions evenly across layers. 1) Location / Service Layer Formula: [Topic] + [City/Area/Country] Example: What is the best [Topic] in [City]? 2) Person Type Layer Formula: [Topic] + [Who they are] Example: What is the best [Topic] for beginners? 3) Demographic Layer Formula: [Topic] + [Age/Gender/Life stage] Example: Which [Topic] is suitable for seniors? 4) Budget Layer Formula: [Topic] + [Price sensitivity] Example: What is the cheapest [Topic]? 5) Problem Layer Formula: [Topic] + [Pain point] Example: Why is my [Topic] not working? 6) Time / Urgency Layer Formula: [Topic] + [Season/Urgency] Example: Can I get instant [Topic] setup? 7) Comparison Layer Formula: [Topic A] vs [Topic B] Example: Is [Topic A] better than [Topic B]? 8) Negative Layer Formula: Why not + [Topic] Example: Why should I avoid cheap [Topic]? 9) Use Case Layer Formula: [Topic] + [Specific scenario] Example: What is the best [Topic] for ecommerce? 10) Outcome Layer Formula: [Topic] + [Desired result] Example: What [Topic] increases sales? 11) Qualifier Layer Formula: Best/Fastest/Easiest + [Topic] + [Context] Example: What is the fastest [Topic] in [Country]? 12) Anti-Audience Layer Formula: [Topic] + [Who it's NOT for] Example: Who should not use [Topic]? OUTPUT FORMAT - Organize by Layer Name - Number each question - Do NOT explain - Return only question queries - Keep questions natural, short, and search-friendly

💡 Best Workflow: Run this first to build FAQ question bank. Then pick top questions and write 40-word direct answers (Koray Rule 28 style) for your FAQ section.

06

Chapter 6 — E-E-A-T & Author Rank

E-E-A-T, Author Entity & Trust Architecture

Build author entities, expertise signals, corroboration pages, and YMYL-proof content that passes Google Quality Rater guidelines.

🏆

P6.1 — Complete Author Entity + E-E-A-T Architecture

Author bio, Person schema, corroboration pages, 90-day authority plan

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are an E-E-A-T and Author Rank specialist. Build a complete author entity strategy for Google. Author name: [YOUR FULL NAME] Niche / expertise: [e.g., "Specialty Coffee, Brewing Methods, Home Barista"] Real credentials: [e.g., "SCA certified, 5 years home barista, tested 40+ coffee makers"] Real experience: [e.g., "Brewed 1,000+ cups, run blind taste tests, personal coffee lab setup"] Published work: [e.g., "200+ articles on coffee brewing, YouTube channel 10K subs"] Third-party mentions: [e.g., "Quoted in Eater.com coffee guide, Reddit AMA on r/Coffee"] Social profiles: [LIST ALL URLS] PART 1 — E-E-A-T SIGNAL AUDIT Score each signal category 1–10, then give specific improvement actions: EXPERIENCE (first-hand involvement): - Personal accounts in content: [score + improvement] - Original data / self-conducted tests: [score + improvement] EXPERTISE (domain knowledge): - Credentials relevance: [score + improvement] - Technical accuracy depth: [score + improvement] AUTHORITATIVENESS (third-party recognition): - External citations and mentions: [score + improvement] - Industry platform presence: [score + improvement] TRUSTWORTHINESS (accuracy + transparency): - Author page completeness: [score + improvement] - Source citation quality: [score + improvement] PART 2 — THREE AUTHOR BIOS 1. Short bio (50 words) — for article bylines 2. Medium bio (150 words) — for author profile page 3. Long bio (400 words) — for dedicated About/Author page Each bio must include verifiable, specific E-E-A-T claims. PART 3 — CORROBORATION PAGE STRATEGY List 10 external platforms where I should build presence. For each: platform name | type of content | E-E-A-T signal it provides | priority PART 4 — PERSON SCHEMA TEMPLATE Generate the complete JSON-LD Person schema markup for my author entity. PART 5 — 90-DAY E-E-A-T BUILDING ROADMAP Month 1: Foundation | Month 2: Evidence | Month 3: Authority

Example — Author Short Bio (Coffee Niche, 50 words) Marcus Chen is an SCA-certified home barista with 5 years of specialty coffee experience. He has personally tested 47 pour over coffee makers and conducted blind taste tests with 200+ participants. His brewing guides reach 50,000 monthly readers.

E-E-A-T signals: ✓ Experience (5 years, 47 devices) ✓ Expertise (SCA certification) ✓ Authority (50K readers) ✓ Trust (verifiable numbers)

📜

P6.2 — Google Quality Rater Simulation + YMYL Review

Full quality rater evaluation, Needs Met rating, improvement plan

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Google Search Quality Rater evaluating content per Google's Search Quality Evaluator Guidelines. Topic: [YOUR TOPIC — state if YMYL: health/finance/legal/safety: YES/NO] Page title: [YOUR TITLE] Author name + credentials: [AUTHOR INFO] Content: [PASTE FULL CONTENT] EVALUATION 1 — PAGE QUALITY RATING Rate each dimension 1–5: - Beneficial Purpose [score + reasoning] - Experience: First-hand evidence visible? [score + reasoning] - Expertise: Formal or demonstrated knowledge? [score + reasoning] - Authoritativeness: Third-party recognition? [score + reasoning] - Trustworthiness: Accurate, transparent? [score + reasoning] - Main Content Quality: Comprehensive, original? [score + reasoning] - YMYL Strictness (if applicable): Meets stricter standards? [score] Overall Page Quality: Lowest / Low / Medium / High / Highest EVALUATION 2 — NEEDS MET RATING Rate: Fails / Slightly Meets / Moderately Meets / Highly Meets / Fully Meets What is missing to achieve "Fully Meets"? EVALUATION 3 — AUTHOR CREDIBILITY CHECK - Is the author identifiable and verifiable? [Y/N + reasoning] - Are credentials relevant to this specific topic? [Y/N] - Red flags identified (if any)? EVALUATION 4 — IMPROVEMENT PLAN Top 5 specific changes to move this page to "Highest": | Change | Why it matters | Implementation steps | Impact (High/Med/Low) |

07

Chapter 7 — Location Coverage Map

Local SEO — Location Entity Coverage

Build topical authority through systematic geographic entity coverage — counties, cities, neighborhoods, and hyper-local content.

📍

P7.1 — Complete Location Topical Map

Full geographic entity hierarchy — State → County → City → Neighborhood

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Local Semantic SEO expert. Build a complete location topical map. Business type / service: [e.g., "Plumbing Repair & Installation"] Primary city: [e.g., "Los Angeles, California"] Service radius / all service areas: [e.g., "30 miles — covering LA County + parts of Orange County"] Business entity name: [YOUR BUSINESS NAME] Is this a YMYL service? [YES/NO + reason] LOCATION ENTITY HIERARCHY Level 1 — State/Region: - State entity attributes (population, regulatory context, key data points) - State-level service page topics (3–5 pages) Level 2 — Counties: - List all counties within service radius - For each county: key attributes, unique search behaviors, page topic Level 3 — Cities: - All incorporated cities, prioritized by: population + search demand - For each city: entity attributes to mention, local landmarks, city-specific needs Level 4 — Neighborhoods (for top 3 cities): - Sub-city neighborhoods that are distinct search entities - For each: unique geographic identity, population center, service context LOCATION PAGE ARCHITECTURE | Page Type | URL Pattern | H1 Template | Key Entities to Mention | Priority | LOCAL QUERY TEMPLATES Generate all local query templates for my service: - [service] in [location] - [location] [service] company - emergency [service] [city] - best [service] [city] reviews - licensed [service] [county] Generate autocomplete variations A–Z for: "[service] in [city] ..." LOCAL E-E-A-T SIGNALS List 10 location-specific trust signals to include on every city page.

Example — Plumber Location Map (Los Angeles) Level 2 Counties: Los Angeles County (primary), Orange County (secondary), Ventura County (partial)
Priority Cities: Los Angeles → Long Beach → Glendale → Santa Monica → Pasadena → Burbank
City Page H1: "Licensed Plumbers in Glendale, CA — Same-Day Service Available"
Local entities to mention: Glendale Water & Power, Verdugo Hills, Brand Boulevard, Glendale Municipal Code

🏙️

P7.2 — Local Semantic Content Page Writer

Write city/neighborhood pages with geographic entity depth and local semantic signals

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a local semantic SEO content writer. Write a city service page with deep geographic entity coverage. Service: [e.g., "Emergency Plumbing Repair"] City: [e.g., "Glendale, California"] Neighborhoods served: [e.g., "Montrose, Adams Hill, Rossmoyne, Verdugo Woodlands, Sparr Heights"] Local landmarks/entities: [e.g., "Glendale Water & Power, Brand Park, Americana at Brand, Verdugo Hills"] Business Name: [YOUR BUSINESS] Service URL target: [e.g., "/emergency-plumber-glendale-ca"] PAGE STRUCTURE Title Tag (60 chars): "[Service] in [City] — [Value Prop]" Meta Description (155 chars): entity + benefit + local signal + CTA H1: Unique from title — includes city entity + service entity H2.1: What is [Service] in [City]? → Define the service in the context of this specific city → Mention city-specific factors: local water hardness, building codes, common local problems → Reference local government entities H2.2: [City] Areas We Serve → List ALL neighborhoods/districts with 1–2 unique geographic notes for each → Also list: major streets, zip codes, nearby landmarks H2.3: Local [Service] Needs in [City] → What specific problems are common in THIS city? → Reference city infrastructure, local building age, local geology, climate → Add 2–3 local statistics H2.4: Why [City] Residents Choose [Business Name] → Specific local trust signals → Response time to this city specifically H2.5: FAQ — [City]-Specific Questions → 5 questions unique to this city/area → Each answer: 40 words max (Rule 28), direct and declarative (Rule 29) SEMANTIC RULES TO APPLY: ✓ Every paragraph must include at least ONE local entity ✓ Use exact local data (zip codes, population, establishment year) ✓ All headings in question format (Rule 8) ✓ Answers in first sentence of each section (Rule 9) ✓ Exact numbers (Rule 31): response times, years in service, etc. Target: 900–1,200 words

08

Chapter 8 — AI Agent Toolkit

AI Agent Workflows for Semantic SEO

Linguistic analysis, NLP proofreading, entity extraction, topical authority scoring, schema generation — full AI-powered workflows.

🤖

P8.1 — Linguistic Sentence-Level Content Audit

Algorithmic authorship check — IF statements, filler words, passive voice, nested clauses

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a linguistic content quality auditor for Semantic SEO. Perform a detailed sentence-level audit following Koray's Algorithmic Authorship standards. Content to audit: [PASTE YOUR CONTENT HERE] SCAN 1 — IF-STATEMENT POSITION VIOLATIONS (Rule 37) Find every sentence starting with "If" or "When". | Original sentence | Fixed version (condition moved to end) | SCAN 2 — FILLER & TRANSITION WORD VIOLATIONS (Rules 13, 14, 30) Find every use of: also, additionally, furthermore, moreover, however (as filler), basically, simply, really, very, quite, just | Sentence with filler | Fixed version without filler | SCAN 3 — DECLARATIVE HEADING CHECK (Rule 8) Find all H2/H3 headings that are declarative statements (not questions). | Declarative heading → Question format version | SCAN 4 — NESTED/COMPLEX SENTENCES (Rule 12) Find sentences with 3+ clauses or over 20 words. | Long sentence (word count) | Split into 2 shorter sentences | SCAN 5 — PLURAL NOUNS WITHOUT EXAMPLES (Rule 34) Find "there are [plural noun]" or "[plural noun] include" without immediate concrete examples. | Violation sentence | Fixed version with examples added | SCAN 6 — PASSIVE VOICE (Rules 3, 33) Find all passive constructions: "was [verb]ed by", "is [verb]ed", "are [verb]ed" | Passive sentence | Active version | SCAN 7 — HEDGING LANGUAGE (Rule 29) Find: might, could, may, perhaps, possibly, it seems, it appears, arguably | Hedging sentence | Certain declarative version | SCAN 8 — VAGUE QUANTITIES (Rule 31) Find: many, some, a few, several, often, sometimes, numerous, various | Vague sentence | Specific numeric version | SUMMARY: Total violations by type | Top 5 priority fixes | Clean score (violations per 100 words)

🧠

P8.2 — Topical Authority Score & Coverage Audit

Measure your topical map completeness, identify gaps, get a 3-month roadmap

ChatGPTClaudeGemini

▸ Full Prompt — Copy & Paste

You are a Topical Authority measurement specialist. Audit my website's semantic coverage. My niche: [e.g., "Pour Over Coffee Equipment & Brewing"] Central entity: [e.g., "Pour Over Coffee"] My published pages (list titles or URLs): [PASTE YOUR PAGE LIST] Authority source website: [COMPETITOR URL] Authority source topics (from their sitemap): [PASTE THEIR TOPIC LIST] AUDIT 1 — COVERAGE COMPLETENESS Based on a complete topical universe for my niche: | Topic | My Status (Covered/Partial/Missing) | Importance (1–10) | Calculate overall coverage score: ___% of total topical universe AUDIT 2 — VASTNESS (BREADTH) How many distinct topic clusters do I cover vs. should cover? Which entire topic clusters am I missing? List the 10 most important uncovered topics. AUDIT 3 — DEPTH ANALYSIS For my top 5 topics, how many supporting pages exist? Ideal: 1 pillar + 5–10 supporting pages per cluster. | Topic | My Pages | Target Pages | Gap | AUDIT 4 — SEMANTIC CONTENT NETWORK (SCN) HEALTH Based on my page list, identify: - 5 pages that should link to each other but probably don't - 3 topic clusters that need a pillar page - 3 orphan topics (covered but with no supporting pages) AUDIT 5 — COMPETITOR GAP TABLE | Topic | Their Depth | My Priority | Effort Level | 3-MONTH CONTENT ROADMAP Month 1 — Critical Gaps (8 pages): [list with reasoning] Month 2 — Depth Building (6 pages): [list] Month 3 — Breadth Expansion (6 pages): [list] Publishing order logic: Foundation before depth before breadth.

💡 Run Monthly: Feed in your updated page list every month to track topical authority growth. This is the closest thing to a "topical authority score" you can generate without specialized tools.

⚡

P8.3 — MASTER PROMPT: Full Semantic SEO Workflow (All 8 Chapters)

Complete end-to-end — Topical Map + Brief + Article + E-E-A-T in one mega prompt

ChatGPTClaudeGemini⚡ Master

▸ MASTER Prompt — Complete Workflow (Use for New Website / New Niche)

You are a complete Semantic SEO system trained in Koray Tugberk GUBUR's framework. Execute a full workflow. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ INPUT DATA ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Website niche: [e.g., "Specialty Coffee Equipment & Home Brewing"] Business type: [B2B / B2C / Local / Ecommerce / Informational Blog] Target audience: [e.g., "Home coffee enthusiasts, beginner to intermediate"] Main product/service: [e.g., "Affiliate coffee gear reviews + brewing guides"] Target region/language: [e.g., "United States, English"] Website stage: [New site / Existing site — X months old] Top 3 competitors: [URL 1, URL 2, URL 3] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PHASE 1 — TOPICAL MAP FOUNDATION ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1a. Identify the CENTRAL ENTITY with full ontology (parent/child/sibling/attributes) 1b. Define 6–8 CORE SECTION topics (the primary content pillars) 1c. Define 6–8 OUTER SECTION topics (peripheral but relevant) 1d. Define TOPICAL BORDERS — 10 topics I must NOT cover and why 1e. Perform FRAME SEMANTICS analysis — 5 key frames in my niche ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PHASE 2 — FIRST 20 PAGES TO PUBLISH ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ | ID | Proposed H1 | Target Query | Intent | Page Type | Priority | Est. Word Count | Links To | Explain the logic behind the order. Show the internal linking architecture for these 20 pages. Suggest a 3-month publishing calendar. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PHASE 3 — CONTENT BRIEF FOR #1 PRIORITY PAGE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ - Title tag + meta description + H1 + URL slug - Complete heading hierarchy (H1→H2→H3) - 15 questions to answer (with format and priority) - Must-mention entities with attribute values - 3 internal link suggestions with anchor text - Evidence requirements per section ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PHASE 4 — SAMPLE CONTENT (Semantic Writing Rules Applied) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4a. Introduction paragraph (150 words) 4b. One complete H2 section (300 words) — show how rules R03, R08, R09, R12, R21, R26, R28, R31, R34 are applied 4c. FAQ section (5 questions × 40 words each) Label every sentence in 4b with the rule it demonstrates. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PHASE 5 — E-E-A-T FOUNDATION ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5a. Top 10 E-E-A-T improvements specific to my niche 5b. Author entity requirements (what credentials Google expects) 5c. YMYL assessment: Is this niche YMYL? What extra standards apply? 5d. 5 corroboration platforms most valuable for this niche

When to Use This Master Prompt

Use P8.3 when: starting a brand new website, entering a new niche, presenting an SEO strategy to a client, doing a full site audit from scratch, or when you want a comprehensive strategy document in one output. Expected output length: 2,000–4,000 words. Use GPT-4o, Claude Sonnet, or Gemini Ultra for best results. Split at each PHASE marker if context limits are hit.

💡 Most Powerful Prompt in This Library. It covers all 8 chapters of the Semantic SEO Guide in one workflow. Start here for any new project.

Back to the Guide