--- name: geo-report description: Generate a professional, client-facing GEO report combining all audit results into a single deliverable with scores, findings, and prioritized actions category: seo risk: safe source: https://github.com/zubair-trabzada/geo-seo-claude source_repo: zubair-trabzada/geo-seo-claude source_type: community date_added: '2026-09-20' license: MIT license_source: https://github.com/zubair-trabzada/geo-seo-claude/blob/main/LICENSE compatibility: Docs-only; upstream helper scripts and templates are not bundled. Site audits need network access to the target site; PDF reports need pandoc and headless Chrome. version: 1.0.0 author: geo-seo-claude tags: - geo - report - client-deliverable - executive-summary - action-plan allowed-tools: Read, Grep, Glob, Bash, WebFetch, Write --- # GEO Client Report Generator ## Purpose This skill aggregates outputs from all GEO audit skills into a single, professional report that can be delivered directly to a client or stakeholder. The report is written for **business owners and marketing leaders**, not developers — technical findings are translated into business impact and clear action items with priority levels. ## How to Use This Skill 1. Run the following audits first (or use existing report data): - `geo-platform-optimizer` -> GEO-PLATFORM-OPTIMIZATION.md - `geo-schema` -> GEO-SCHEMA-REPORT.md - `geo-technical` -> GEO-TECHNICAL-AUDIT.md - `geo-content` -> GEO-CONTENT-ANALYSIS.md - (Optional) `geo-llmstxt` -> llms.txt assessment - (Optional) `geo-brand-mentions` -> brand authority data 2. Collect all scores and findings 3. Calculate the composite GEO Readiness Score 4. Generate the client report using the template below 5. Output: GEO-CLIENT-REPORT.md --- ## GEO Readiness Score Calculation ### Component Weights | Component | Weight | Source Skill | |---|---|---| | AI Platform Readiness | 25% | geo-platform-optimizer | | Content Quality & E-E-A-T | 25% | geo-content | | Technical Foundation | 20% | geo-technical | | Schema & Structured Data | 15% | geo-schema | | Brand Authority & Entity Presence | 15% | geo-platform-optimizer (entity signals) | ### Score Formula ``` GEO Score = (Platform Score * 0.25) + (Content Score * 0.25) + (Technical Score * 0.20) + (Schema Score * 0.15) + (Brand Score * 0.15) ``` Validate each available component in [0,100] and round only the final sum. These weights are an editorial rubric, not a platform-endorsed ranking or citation probability. Missing audits are N/A, not zero; do not publish a comparable composite unless all five components use the same rubric/scope/date. Example: five scores of 80 yield 80/100; this does not predict 80% citation likelihood. ### Score Interpretation for Clients | Score Range | Label | Client-Facing Description | |---|---|---| | 85-100 | Excellent | Few gaps under the documented audit rubric; actual visibility unmeasured unless separately sampled. | | 70-84 | Good | Several documented improvements remain. | | 55-69 | Moderate | Review the observed gaps and coverage limits. | | 40-54 | Below Average | Many rubric checks need attention; no competitive-loss inference follows. | | 0-39 | Needs Attention | Prioritize verified access/content defects; score alone does not prove invisibility. | --- ## Report Template The complete report follows this exact structure. Each section includes instructions on what to write and how. --- ### Section 1: Executive Summary Write exactly ONE paragraph (4-6 sentences) covering: - What was analyzed (domain, number of pages, date of analysis) - The overall GEO Readiness Score with context ("XX/100, which places [brand] in the [label] tier") - The single most impactful finding (positive or negative) - Top 3 priority recommendations in one sentence - One evidence-supported business implication. Include monetary scenarios only with measured baseline, explicit assumptions and uncertainty; otherwise state impact unmeasured. **Tone**: Confident, direct, professional. No jargon. Distinguish observations, uncertainty and hypotheses. Write as a consultant delivering findings, not as a tool generating a report. ### Section 2: GEO Readiness Score Present the overall score prominently: ``` ## GEO Readiness Score: XX/100 — [Label] ``` Then break down by component in a table: ```markdown | Component | Score | Weight | Weighted Score | |---|---|---|---| | AI Platform Readiness | XX/100 | 25% | XX | | Content Quality & E-E-A-T | XX/100 | 25% | XX | | Technical Foundation | XX/100 | 20% | XX | | Schema & Structured Data | XX/100 | 15% | XX | | Brand Authority | XX/100 | 15% | XX | | **Overall** | | | **XX/100** | ``` ### Section 3: AI Visibility Dashboard Present per-platform readiness scores: ```markdown ## AI Visibility Dashboard | AI Platform | Readiness Score | Key Gap | Priority Action | |---|---|---|---| | Google AI Overviews | XX/100 | [One-line gap] | [One-line action] | | ChatGPT Web Search | XX/100 | [One-line gap] | [One-line action] | | Perplexity AI | XX/100 | [One-line gap] | [One-line action] | | Google Gemini | XX/100 | [One-line gap] | [One-line action] | | Bing Copilot | XX/100 | [One-line gap] | [One-line action] | ``` Add a brief paragraph explaining what these scores mean: "These scores summarize checks in our disclosed rubric; they do not estimate citation probability. Report measured citations separately with prompt set, locale, date, account/mode and sampling limitations." ### Section 4: AI Crawler Access Status Present as a clear table: ```markdown ## AI Crawler Access | AI Crawler | Platform | Status | Impact | Recommendation | |---|---|---|---|---| | Googlebot | Google Search + AIO | Allowed/Blocked | Critical | [Action] | | OAI-SearchBot | OpenAI search discovery | Allowed/Blocked/Unknown | [Observed effect] | [Action] | | GPTBot | OpenAI model-training crawl | Allowed/Blocked/Unknown | Policy choice | [Action] | | Bingbot | Bing + Copilot + ChatGPT | Allowed/Blocked | High | [Action] | | PerplexityBot | Perplexity AI | Allowed/Blocked | Medium | [Action] | | Google-Extended | Gemini Training | Allowed/Blocked | Medium | [Action] | | ClaudeBot | Anthropic Claude | Allowed/Blocked | Medium | [Action] | | Applebot-Extended | Apple Intelligence | Allowed/Blocked | Medium | [Action] | ``` **Translate for the client**: Distinguish search discovery, user-requested fetching and training controls using current vendor documentation. Allowing training is not required for search eligibility. Respect the owner’s licensing/privacy opt-outs; robots rules do not guarantee crawling, indexing, citation or access control. ### Section 5: Brand Authority Analysis Present entity presence across platforms: ```markdown ## Brand Authority | Platform | Presence | Status | Impact on AI Visibility | |---|---|---|---| | Wikipedia | Yes/No | [Detail] | [Observed relevance; no universal citation share] | | Wikidata | Yes/No | [Detail] | High — machine-readable entity data | | LinkedIn | Yes/No | [Detail] | High — Bing Copilot and ChatGPT signal | | YouTube | Yes/No | [Detail] | High — Gemini and Perplexity signal | | Reddit | Yes/No | [Detail] | [Observed relevance; no universal citation share] | | Google Knowledge Panel | Yes/No | [Detail] | High — Gemini entity recognition | | Crunchbase | Yes/No | [Detail] | Medium — entity validation | | GitHub | Yes/No | [Detail] | Medium — tech brand signal | ``` **Translate for the client**: "AI platforms build trust by cross-referencing your brand across multiple authoritative sources. Accurate relevant profiles help readers verify identity; no causal citation increase is established by profile count alone." ### Section 6: Citability Analysis #### Top 5 Most Citable Pages For each page: - URL - Why it is citable (structure, depth, E-E-A-T signals) - One specific improvement that would make it even more citable #### Top 5 Least Citable Pages For each page: - URL - Why it is unlikely to be cited (thin content, poor structure, missing signals) - Specific rewrite or restructure recommendation **Business impact framing**: "Your most citable pages are your best candidates for appearing in AI-generated answers. Prioritize those pages only after assessing audience need, observed defects, effort and measured outcomes." ### Section 7: Technical Health Summary Present the key technical findings in business-friendly language: ```markdown ## Technical Health | Area | Status | Business Impact | |---|---|---| | Core Web Vitals | Good/Needs Work/Poor | [Impact on user experience and rankings] | | Server-Side Rendering | Yes/Partial/No | [Impact on AI crawler visibility] | | Mobile Optimization | Good/Needs Work/Poor | [Impact on Google's mobile-first indexing] | | Security (HTTPS + Headers) | Good/Needs Work/Poor | [Impact on trust signals] | | Page Speed | Fast/Average/Slow | [Impact on user experience and crawl budget] | | IndexNow Protocol | Implemented/Not | [Impact on Bing/ChatGPT indexing speed] | ``` **Rendering finding**: Compare fetched HTML and rendered content for representative URLs and named crawlers. Client-side rendering does not by itself prove an empty page, exclusion or the highest-impact defect. Report observed missing content and rendering limitations. ### Section 8: Schema & Structured Data ```markdown ## Schema & Structured Data ### Current Implementation | Schema Type | Present | Status | AI Impact | |---|---|---|---| | Organization | Yes/No | [Valid/Issues] | Critical — entity recognition | | Article + Author | Yes/No | [Valid/Issues] | High — E-E-A-T signal | | sameAs (entity links) | Yes/No | [Count] links | Critical — cross-platform entity graph | | [Business-specific] | Yes/No | [Valid/Issues] | [Impact] | | WebSite | Yes/No | [Valid/Issues] | [Applicable use; Google sitelinks search box retired in 2024] | | BreadcrumbList | Yes/No | [Valid/Issues] | Low-Medium — navigation context | ``` Only claim code is prepared if actual reviewed markup is included and matches visible content. Valid schema is not a promise of rich results or AI citation. ### Section 9: llms.txt Status ```markdown ## llms.txt — AI Content Guide | File | Status | Recommendation | |---|---|---| | /llms.txt | Present/Missing | [Action] | | /llms-full.txt | Present/Missing | [Action] | ``` **Translate for the client**: "llms.txt is a proposal for a content guide, not robots access control or a required AI-search eligibility file. No adoption, ranking or competitive benefit is implied; treat implementation as optional and avoid publishing private content." ### Section 10: Prioritized Action Plan This is the most important section of the report. Organize actions by timeline and impact. ```markdown ## Prioritized Action Plan ### Quick Wins (This Week) *High impact, low effort — can be implemented immediately* | # | Action | Impact | Effort | Platforms Affected | |---|---|---|---|---| | 1 | [Specific action] | [High/Med] | [Hours estimate] | [Which AI platforms] | | 2 | [Specific action] | [High/Med] | [Hours estimate] | [Which AI platforms] | ``` **Quick Win criteria**: Can be done in < 4 hours by one person. Examples: - Unblock AI crawlers in robots.txt - Add publication dates to existing content - Add author bylines with credentials - Fix broken meta descriptions - Add sameAs properties to existing Organization schema - Create/claim llms.txt file ```markdown ### Medium-Term Improvements (This Month) *Significant impact, moderate effort — requires content or technical changes* | # | Action | Impact | Effort | Platforms Affected | |---|---|---|---|---| | 1 | [Specific action] | [High/Med] | [Days estimate] | [Which AI platforms] | ``` **Medium-Term criteria**: 1-5 days of work. Examples: - Restructure top 10 pages with question-based headings and direct answers - Implement comprehensive Schema.org markup - Create author pages with credentials and sameAs links - Optimize Core Web Vitals (image compression, code splitting) - Register and configure Bing Webmaster Tools - Implement IndexNow protocol ```markdown ### Strategic Initiatives (This Quarter) *Long-term competitive advantage, requires ongoing investment* | # | Action | Impact | Effort | Platforms Affected | |---|---|---|---|---| | 1 | [Specific action] | [High/Med] | [Weeks estimate] | [Which AI platforms] | ``` **Strategic criteria**: Ongoing effort over weeks/months. Examples: - Build Wikipedia/Wikidata entity presence - Develop active Reddit community engagement strategy - Create YouTube content strategy aligned with search queries - Implement server-side rendering (if currently client-rendered) - Build topical authority through comprehensive content strategy - Establish original research/data publication program ### Estimated Impact After the action plan, include an impact estimate: Use measured baseline data or state “impact not quantified.” Never translate rubric points directly into citation/traffic/revenue lift. An explicitly hypothetical scenario may show the arithmetic: 100 incremental qualified visits × 2% conversion × $50 contribution per conversion = $100/month before implementation cost, assuming those visits and conversions occur. Record attribution window, uncertainty and validation plan; this arithmetic is not a forecast or industry benchmark. ### Section 11: Competitor Comparison (if competitor URLs provided) If competitor URLs were analyzed alongside the primary domain: ```markdown ## Competitor Comparison | Metric | [Your Brand] | [Competitor 1] | [Competitor 2] | |---|---|---|---| | Overall GEO Score | XX/100 | XX/100 | XX/100 | | Google AIO Readiness | XX/100 | XX/100 | XX/100 | | ChatGPT Readiness | XX/100 | XX/100 | XX/100 | | Perplexity Readiness | XX/100 | XX/100 | XX/100 | | Schema Coverage | [Detail] | [Detail] | [Detail] | | Wikipedia Presence | Yes/No | Yes/No | Yes/No | | Reddit Authority | [Detail] | [Detail] | [Detail] | | SSR Status | Yes/No | Yes/No | Yes/No | ### Where You Lead [Specific areas where the brand outperforms competitors] ### Where You Trail [Specific areas where competitors have an advantage, with actions to close the gap] ``` ### Section 12: Appendix ```markdown ## Appendix ### Methodology This GEO audit was conducted using the following methodology: - **Pages analyzed**: [List of specific URLs audited] - **Platforms assessed**: Google AI Overviews, ChatGPT, Perplexity AI, Google Gemini, Bing Copilot - **Technical checks**: HTTP headers, robots.txt, HTML source analysis, structured data validation - **Content assessment**: E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) as a disclosed editorial framework; cite the exact edition actually consulted - **Schema validation**: JSON-LD parsing and Schema.org specification compliance - **Date of analysis**: [Date] ### Data Sources - Google Search Quality Rater Guidelines (actual consulted edition/date/link) - Schema.org full type hierarchy - Only studies actually consulted, with URL, sample/method/date and applicable limitations - Core Web Vitals documentation actually consulted (URL/date) - AI crawler user-agent documentation (per-platform official docs) ### Glossary | Term | Definition | |---|---| | GEO | Generative Engine Optimization — optimizing content to be cited by AI search platforms | | AIO | AI Overviews — Google's AI-generated answer boxes at the top of search results | | E-E-A-T | Experience, Expertise, Authoritativeness, Trustworthiness — Google's content quality framework | | SSR | Server-Side Rendering — generating HTML on the server so crawlers can read content without JavaScript | | CWV | Core Web Vitals — Google's page experience metrics (LCP, INP, CLS) | | LCP | Largest Contentful Paint — time to render the largest visible element | | INP | Interaction to Next Paint — responsiveness metric (replaced FID in March 2024) | | CLS | Cumulative Layout Shift — visual stability metric | | JSON-LD | JavaScript Object Notation for Linked Data — preferred structured data format | | sameAs | Schema.org property linking an entity to its profiles on other platforms | | IndexNow | Protocol for instantly notifying search engines of content changes | | llms.txt | Proposed standard file for guiding AI systems about a site's content | | YMYL | Your Money or Your Life — topics requiring highest E-E-A-T standards | | SERP | Search Engine Results Page | | Topical Authority | The depth and breadth of a site's coverage of its core topic area | ``` --- ## Formatting and Tone Guidelines ### Formatting - Use clean markdown throughout: tables, headers (H2/H3), bullet points, bold for emphasis - Tables for data, bullets for recommendations, bold for key terms - One blank line between sections for readability - Use horizontal rules (---) to separate major sections - All URLs should be absolute (not relative) ### Tone - **Professional but accessible** — written for a business owner, not a developer - **Confident and direct** — state verified observations clearly and label uncertain inferences - **Action-oriented** — every finding should connect to a specific action - **Business-impact focused** — translate technical issues into business outcomes - Avoid: jargon without explanation, unsupported certainty, passive voice, irrelevant caveats - Use: "Your site [does/does not]...", "We recommend...", "This impacts..." ### Dollar-Value Framing Connect recommendations to verified user/business problems and measured baselines. Use the explicit hypothetical arithmetic above only as a scenario, never as evidence that a score increase causes traffic or revenue. Report implementation costs and measurement gaps; never guarantee results. --- ## Output Generate **GEO-CLIENT-REPORT.md** using the complete template above, filled with actual audit data. The report should be: - Appropriate to scope and audience; word count does not imply a fixed page count - Ready for factual/privacy/owner review before authorized delivery - Self-contained (no references to other report files — all relevant data is included) - Printable and presentable (clean markdown formatting) ## When to Use - You need a Generative Engine Optimization task for a website: audit, citability, crawlers, schema, llms.txt, content, platform tuning, or client reporting. - Run read-only analysis first; propose site changes before making any. ## Limitations - Audits are read-only analysis; never publish, deploy, or modify the target site without explicit approval. - Scores and citation likelihoods are heuristics, not guarantees from AI search platforms. - Docs-only import: upstream scripts, agents, hooks, and schema templates are not bundled. ### Example ```bash curl -s https://example.com/robots.txt curl -s https://example.com/llms.txt ``` > Adapted from [zubair-trabzada/geo-seo-claude](https://github.com/zubair-trabzada/geo-seo-claude) (MIT); frontmatter, When to Use/Limitations, and safety boundaries added for upstream compliance. Docs-only import: upstream runtime helpers not bundled. --- Source attribution: zubair-trabzada/geo-seo-claude contributors, via Agentic Awesome Skills Original project: https://github.com/zubair-trabzada/geo-seo-claude License: MIT + CC-BY-4.0 License information: https://creativecommons.org/licenses/by/4.0/ Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Zubair Trabzada Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: zubair-trabzada/geo-seo-claude contributors, via Agentic Awesome Skills Original project: https://github.com/zubair-trabzada/geo-seo-claude Attribution basis: Recorded upstream repository Fields of work: Marketing Roles: SEO Specialist Specialties: Specialty not specified Tools: Tool not specified Country applicability: Country not specified Classification basis: Dave AI task classification from package title, description, and declared metadata Instruction SHA-256: 2fefe423c8f2d54bf8f6b97a11b8e146037d8965ee527f6add379de2578208ea Metadata reviewed: 2026-10-27 This metadata supersedes earlier Mega AI Hub catalog attribution. Original instruction and supporting files are preserved.