geo-gap-fixer

GEO Gap Fixer

Agent skill that audits LLM brand visibility and converts gaps into a concrete GEO content action plan.

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When to Use

Use this skill when a user wants to audit their Generative Engine Optimization (GEO) share-of-voice to know which LLM prompts their brand is losing, understand why competitors are recommended instead, and get a specific content fix plan.

Do NOT use this skill for: general SEO audits, paid ad optimization, or continuous social media monitoring. This is a point-in-time LLM visibility audit.

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Step 1: Inputs

To run the audit, the user must provide API keys and a configuration file. Ensure the following are set up:

1. API Keys: At least 2 of 4 keys must be set in the environment or .env file (OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY, PERPLEXITY_API_KEY).
2. Dependencies: pip install openai anthropic google-genai
3. Config File: config.json (copied from config.example.json) must contain:
   • brand_name (string, required)
   • competitors (list of strings, required, 1-10 entries)
   • category (string, required)
   • buyer_intent_prompts (list of strings, optional. If empty, 20 prompts are auto-generated)
   • target_llms (list of strings, optional)
   • website_url (string, optional)

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Step 2: Execution Pipeline

Run the following scripts in order. Stop and ask for clarification if any script fails.

1. python scripts/probe_llms.py (Optional: append --dry-run to test config without API calls)

   • Sends buyer-intent prompts to the configured LLM APIs.
   • Saves responses to data/raw_responses.json.

2. python scripts/analyze_results.py

   • Analyzes raw responses for brand mentions, ranking, sentiment, and cited domains.
   • Saves structured analysis to data/analysis.json.

3. python scripts/build_report.py

   • Assembles the final 5-section GEO audit report.
   • Saves to report/geo_audit_report.md and report/geo_audit_report.json.