geo-brand-mentions

The geo-brand-mentions skill evaluates a brand's visibility and authority across platforms that influence AI model training and citation, such as YouTube, Reddit, Wikipedia, and LinkedIn. It calculates a Brand Authority Score based on platform-specific metrics and provides a structured analysis of brand presence.

347

Installs

Use cases

5/10

Quality

Is geo-brand-mentions safe to install?

Review the source first

Review the source first: our audit of geo-brand-mentions's source files found 1 shell command, 2 external URLs, no file writes (high risk). Every command and URL listed appears verbatim in the skill's source. The skill executes Python code and makes network requests to Wikipedia and Wikidata APIs.

How we audit skills: our security review methodology.

Who is this skill for?

Marketing professionals, SEO specialists, and brand managers seeking to improve their brand's visibility in AI-generated search results and recommendations.

What can you do with it?

Assess brand entity recognition for AI systems
Identify gaps in cross-platform brand presence
Calculate a quantitative Brand Authority Score
Analyze sentiment and mention volume on Reddit and YouTube
Verify Wikipedia and Wikidata entity status

How good is this skill?

Quality score: 5/10. The skill provides a clear, research-backed methodology for evaluating brand authority in the context of AI search. The instructions are specific and include actionable analysis steps.

What does the skill file contain?

SKILL.md

# Brand Mention Scanner Skill

## Core Insight

Brand mentions correlate approximately 3x more strongly with AI visibility than traditional backlinks. An Ahrefs study published in December 2025, analyzing 75,000 brands across AI search platforms, found that **unlinked brand mentions** -- references to a brand name without a hyperlink -- are a stronger predictor of whether AI systems cite and recommend a brand than Domain Rating or backlink count.

The critical finding: **the platform where the mention appears matters enormously.** Not all mentions are equal. A mention on YouTube or Reddit carr...

Frequently asked questions

Why does the skill prioritize unlinked brand mentions over backlinks?

Research indicates that unlinked brand mentions correlate more strongly with AI visibility and citation decisions than traditional backlink metrics.

How does the skill determine the Brand Authority Score?

It uses a weighted formula: YouTube (25%), Reddit (25%), Wikipedia/Wikidata (20%), LinkedIn (15%), and other platforms (15%).

What platforms are considered most important for AI citation?

YouTube and Reddit are identified as the most critical platforms due to their heavy inclusion in AI training datasets.

Data sourced from zubair-trabzada/geo-seo-claude on GitHub. Install counts from skills.sh. The summary and security audit are derived from the skill's source files: every command and URL listed appears verbatim in the source.

Install

Works with Claude Code, Cursor, Codex CLI, and 50+ agents.

Manual install paths per agent

Claude Code: .claude/skills/ or ~/.claude/skills/

Codex CLI: .codex/skills/ or ~/.codex/skills/

GitHub Copilot: .github/skills/ or ~/.copilot/skills/

Amp: .agents/skills/ or ~/.config/agents/skills/

Copy the skill folder (with SKILL.md) into the project or global directory.

Security audit

high risk

Commands

URLs

File I/O

The skill executes Python code and makes network requests to Wikipedia and Wikidata APIs.

View commands and endpoints

$ python3 -c "import requests, json from urllib.parse import quote_plus brand = '[Brand_Name]' api_url = f'https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch={quote_plus(brand)}&format=json' r = requests.get(api_url, headers={'User-Agent': 'GEO-Audit/1.0'}, timeout=15) data = r.json() results = data.get('query', {}).get('search', []) if results and brand.lower() in results[0].get('title', '').lower(): print(f'WIKIPEDIA PAGE EXISTS: {results[0][\"title\"]}') print(f'URL: https://en.wikipedia.org/wiki/{results[0][\"title\"].replace(\" \", \"_\")}') else: print('No direct Wikipedia page found') wd_url = f'https://www.wikidata.org/w/api.php?action=wbsearchentities&search={quote_plus(brand)}&language=en&format=json' r2 = requests.get(wd_url, headers={'User-Agent': 'GEO-Audit/1.0'}, timeout=15) wd = r2.json()"

https://en.wikipedia.org/w/api.php

https://www.wikidata.org/w/api.php

Sourcezubair-trabzada/geo-seo-claude

Installs347

Quality5/10

SEO GEO Brand-Authority AI-Visibility Marketing-Analytics

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