geo-visibility-audit

Perform manual AI search visibility audits without requiring API tools. Use when auditing brand visibility across AI engines, analyzing competitor presence, or building GEO strategies based on direct AI search testing.

16 stars

Best use case

geo-visibility-audit is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Perform manual AI search visibility audits without requiring API tools. Use when auditing brand visibility across AI engines, analyzing competitor presence, or building GEO strategies based on direct AI search testing.

Teams using geo-visibility-audit should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/geo-visibility-audit/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/development/geo-visibility-audit/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/geo-visibility-audit/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How geo-visibility-audit Compares

Feature / Agentgeo-visibility-auditStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Perform manual AI search visibility audits without requiring API tools. Use when auditing brand visibility across AI engines, analyzing competitor presence, or building GEO strategies based on direct AI search testing.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# GEO Visibility Audit

Perform comprehensive AI search visibility analysis by directly testing AI search engines. This skill provides a systematic approach to auditing without requiring external API tools.

## Why Visibility Audits Matter

Only 16% of brands systematically track AI search performance, creating a significant opportunity gap. Understanding your current visibility baseline is essential for improvement.

**Key statistics:**

- AI-sourced visitors convert at 27% vs 2.1% from traditional search (12x improvement)
- Web mentions correlate 3x more strongly with AI visibility than backlinks
- 40-60% of domains cited in AI answers change within one month
- 26% of brands have zero mentions in AI Overviews

## Visibility Audit Framework

### Step 1: Define Audit Scope

Before testing, define these parameters:

**Brand Information:**

- Primary brand name
- Alternative names/spellings
- Key products/services
- Target markets/regions

**Competitor Set:**

- 3-5 direct competitors
- 2-3 indirect competitors (optional)

**Topic Clusters to Test:**

- Primary category queries ("best [your category]")
- Product-specific queries ("[your product type] features")
- Comparison queries ("[competitor A] vs [competitor B]")
- How-to/educational queries ("how to [your use case]")

### Step 2: Test Across AI Platforms

Test your defined queries across these platforms:

| Platform       | Access               | Citation Style      | Notes                      |
| -------------- | -------------------- | ------------------- | -------------------------- |
| ChatGPT        | chat.openai.com      | 3-4 citations avg   | Highest search volume      |
| Perplexity     | perplexity.ai        | 13 citations avg    | Shows sources prominently  |
| Google AI Mode | google.com (AI Mode) | Integrated results  | Affects traditional search |
| Claude         | claude.ai            | Conversational      | Growing user base          |
| Bing Copilot   | bing.com             | Microsoft ecosystem | Enterprise users           |

**For each query, document:**

1. Is your brand mentioned?
2. How is your brand described (accurate/inaccurate)?
3. Which competitors are mentioned?
4. What sources are cited?
5. What position does your brand appear (if mentioned)?

### Step 3: Query Testing Template

Use these query patterns for comprehensive coverage:

**Category Queries:**

```
"What are the best [your category]?"
"Top [your category] in 2026"
"[Your category] comparison"
```

**Product Queries:**

```
"What is [your product]?"
"How does [your product] work?"
"[Your product] features"
"[Your product] pricing"
```

**Comparison Queries:**

```
"[Your brand] vs [competitor]"
"[Competitor A] vs [Competitor B] vs [Competitor C]"
"Best [your category] comparison"
```

**How-To Queries:**

```
"How to [your use case]"
"[Your category] tutorial"
"[Your category] getting started"
```

### Step 4: Record Visibility Data

Create a tracking spreadsheet with these columns:

| Query   | Platform | Brand Mentioned | Position    | Description Accurate | Competitors Mentioned | Sources Cited |
| ------- | -------- | --------------- | ----------- | -------------------- | --------------------- | ------------- |
| [query] | ChatGPT  | Yes/No          | 1st/2nd/etc | Yes/No/Partial       | [list]                | [list]        |

### Step 5: Analyze Key Metrics

Calculate these metrics from your testing:

#### Brand Visibility Rate

```
Visibility % = (Queries where brand mentioned / Total queries tested) × 100
```

**Benchmarks:**
| Visibility | Rating | Interpretation |
|------------|--------|----------------|
| > 30% | Excellent | Strong AI presence |
| 20-30% | Good | Solid foundation |
| 10-20% | Fair | Room for improvement |
| < 10% | Poor | Significant gap |

#### Context Accuracy Rate

```
Accuracy % = (Accurate descriptions / Total mentions) × 100
```

Target: 95%+ accuracy

**Check for:**

- Correct product descriptions
- Accurate pricing information
- Current feature lists
- Proper brand positioning
- No outdated information

#### Competitive Share of Voice

```
SOV % = (Your mentions / Total competitor mentions) × 100
```

**Benchmarks:**
| Share of Voice | Position |
|----------------|----------|
| > 25% | Category leader |
| 15-25% | Major player |
| 5-15% | Competitive |
| < 5% | Visibility gap |

### Step 6: Gap Analysis

Identify where competitors appear but you don't:

**Create a gap matrix:**

| Query Topic | Your Visibility | Competitor A | Competitor B | Gap Severity |
| ----------- | --------------- | ------------ | ------------ | ------------ |
| [topic]     | 0%              | 40%          | 30%          | Critical     |
| [topic]     | 20%             | 50%          | 40%          | High         |
| [topic]     | 40%             | 45%          | 35%          | Moderate     |

**Gap categories:**

1. **Complete absence** - You never appear (critical priority)
2. **Weak presence** - You appear < 10% vs competitor > 30% (high priority)
3. **Competitive** - Similar visibility (maintain/optimize)
4. **Leadership** - You dominate (protect and expand)

### Step 7: Citation Source Analysis

Document which sources AI systems cite:

**Common citation sources:**

- Wikipedia/Wikidata
- Industry publications
- Review sites (G2, Capterra, Trustpilot)
- Reddit discussions
- YouTube videos
- LinkedIn articles
- Official documentation

**Identify gaps:**

- Sources citing competitors but not you
- Sources you could target for mentions
- Missing presence on key platforms

### Step 8: Engine-by-Engine Comparison

Compare your performance across platforms:

| Engine     | Your Visibility | Top Competitor | Gap | Priority     |
| ---------- | --------------- | -------------- | --- | ------------ |
| ChatGPT    | \_%             | \_%            | \_% | High/Med/Low |
| Perplexity | \_%             | \_%            | \_% | High/Med/Low |
| Google AI  | \_%             | \_%            | \_% | High/Med/Low |
| Claude     | \_%             | \_%            | \_% | High/Med/Low |

## Audit Report Template

```markdown
# AI Search Visibility Audit Report

**Brand:** [Brand Name]
**Date:** [Date]
**Queries Tested:** [Number]
**Platforms Tested:** [List]

## Executive Summary

[2-3 paragraph summary of key findings]

## Key Metrics

| Metric           | Current | Target | Status |
| ---------------- | ------- | ------ | ------ |
| Brand Visibility | X%      | 30%+   | ✓/✗    |
| Context Accuracy | X%      | 95%+   | ✓/✗    |
| Share of Voice   | X%      | 15%+   | ✓/✗    |

## Visibility by Platform

| Platform   | Visibility | Accuracy | Notes   |
| ---------- | ---------- | -------- | ------- |
| ChatGPT    | X%         | X%       | [notes] |
| Perplexity | X%         | X%       | [notes] |
| Google AI  | X%         | X%       | [notes] |

## Competitor Comparison

| Competitor     | Visibility | SOV    | Key Advantages  |
| -------------- | ---------- | ------ | --------------- |
| Competitor A   | X%         | X%     | [advantages]    |
| Competitor B   | X%         | X%     | [advantages]    |
| **Your Brand** | **X%**     | **X%** | [current state] |

## Top Visibility Gaps

1. **[Query/Topic]**

   - Your visibility: X%
   - Top competitor: X% (Competitor A)
   - Opportunity: [Description]
   - Priority: Critical/High/Medium

2. **[Query/Topic]**
   - Your visibility: X%
   - Top competitor: X%
   - Opportunity: [Description]
   - Priority: Critical/High/Medium

## Context Accuracy Issues

- [ ] [Issue 1: e.g., "Outdated pricing mentioned"]
- [ ] [Issue 2: e.g., "Missing key product feature"]
- [ ] [Issue 3: e.g., "Incorrect company description"]

## Citation Source Gaps

**Currently citing your brand:**

- [Source 1]
- [Source 2]

**Citing competitors but not you:**

- [Source 1] - Cites: [Competitor A, B]
- [Source 2] - Cites: [Competitor A]

## Recommendations

### Immediate Actions (This Week)

1. [Specific action with expected impact]
2. [Specific action with expected impact]

### Short-Term (This Month)

1. [Specific action with expected impact]
2. [Specific action with expected impact]

### Medium-Term (This Quarter)

1. [Specific action with expected impact]
2. [Specific action with expected impact]

## Next Audit Date

[Schedule: Monthly recommended]
```

## Action Planning Based on Findings

### Quick Wins (1-2 weeks)

- Update outdated content on high-visibility pages
- Fix context accuracy issues
- Add missing schema markup
- Refresh dates on cornerstone content

### Medium Priority (1-3 months)

- Create content for visibility gap topics
- Build presence on citation source sites
- Develop comparison content
- Expand FAQ coverage

### Strategic Initiatives (3-6 months)

- Build third-party authority (PR, partnerships)
- Develop original research/data
- Create comprehensive resource hubs
- Establish thought leadership content

## Ongoing Monitoring Cadence

| Check                  | Frequency | Purpose                    |
| ---------------------- | --------- | -------------------------- |
| Quick visibility check | Weekly    | Spot major changes         |
| Full query testing     | Bi-weekly | Track trends               |
| Competitor review      | Monthly   | Monitor competitive shifts |
| Full audit             | Quarterly | Comprehensive assessment   |

## Tips for Effective Testing

1. **Use incognito/private browsing** to avoid personalized results
2. **Test at different times** to account for variation
3. **Document exact query phrasing** for consistent retesting
4. **Screenshot responses** for evidence and comparison
5. **Note response dates** to track freshness of AI answers
6. **Test on mobile and desktop** for different experiences

Related Skills

rule-auditor

16
from diegosouzapw/awesome-omni-skill

Validates code against currently loaded rules and reports compliance violations. Supports auto-fixing violations with confirmation, dry-run mode, and automatic backups. Use after implementing features, during code review, or to ensure coding standards are followed. Provides actionable feedback with line-by-line issues and suggested fixes.

production-code-audit

16
from diegosouzapw/awesome-omni-skill

Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations

config-audit

16
from diegosouzapw/awesome-omni-skill

This skill should be used when auditing or comparing Claude Code and Cursor IDE configurations to identify feature gaps, equivalencies, and migration opportunities. Useful when managing AI development tooling across both platforms or deciding how to structure AI workflows.

code-audit

16
from diegosouzapw/awesome-omni-skill

Perform a human-assisted code audit. Use when asked to audit, review architecture, document a codebase, or create technical documentation with diagrams.

calendar-audit

16
from diegosouzapw/awesome-omni-skill

Protect your deep work time. Calendar Audit scores every meeting on your calendar, calculates your deep work gap, and makes specific suggestions to reclaim focus time. Supports multiple calendar tools (screenshot, Google Calendar MCP, Apple Calendar, icalBuddy, gcalcli) and scoring frameworks (5-Dimension, Eisenhower, RACI, Value vs Effort, Custom). Value first — your first audit takes 2 minutes with just a screenshot. Just say "calendar-audit" to get going.

auditor-frontend-ui-ux

16
from diegosouzapw/awesome-omni-skill

Audit frontend code quality, UI/UX, forms, state management, and translations. Typically loaded by the audit-orchestrator skill via sub-agents, but can be used standalone.

audit_logging

16
from diegosouzapw/awesome-omni-skill

Ensure every critical action is logged (vital for UAG/Trust Room).

audit-code

16
from diegosouzapw/awesome-omni-skill

Run a single-session code review audit on the codebase

architecture-auditor

16
from diegosouzapw/awesome-omni-skill

Architecture audit and analysis specialist for Modular Monoliths. **ALWAYS use when reviewing codebase architecture, evaluating bounded contexts, assessing shared kernel size, detecting "Core Obesity Syndrome", or comparing implementation against ADR-0001 and anti-patterns guide.** Use proactively when user asks about context isolation, cross-context coupling, or shared kernel growth. Examples - "audit contexts structure", "check shared kernel size", "find cross-context imports", "detect base classes", "review bounded context isolation", "check for Core Obesity".

ux-audit

16
from diegosouzapw/awesome-omni-skill

AI skill for automated design audits. Evaluate interfaces against proven UX principles for visual hierarchy, accessibility, cognitive load, navigation, and more. Based on Making UX Decisions by Tommy Geoco.

Audit UI/UX Consistency

16
from diegosouzapw/awesome-omni-skill

COMPREHENSIVE UI/UX audit combining code analysis AND visual screenshot analysis. Detects design system violations, visual inconsistencies across views, button/card/modal style variants, color palette chaos, theme breaks, and accessibility issues. Provides detailed visual evidence and prioritized fixes. INCLUDES Storybook design decision workflow for user-driven choices. CRITICAL - Must analyze actual rendered screenshots, not just code.

audit-style

16
from diegosouzapw/awesome-omni-skill

Audit and refactor CSS to comply with Game Loopers design system and BEM methodology