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geo-report

Marketing & growth

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Updated 10-29 03:50

About this skill

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 Missing audits are N/A, not zero; do not publish a comparable composite unless all five components use the same rubric/scope/date.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:

| 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:

## 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:

## 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:

## 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:

## 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

## 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

## 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.

## 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
### 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
### 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:

## 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

## 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

curl -s https://example.com/robots.txt
curl -s https://example.com/llms.txt

Adapted from 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.