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aeo-prompt-frequency-analyzer

Analyze what search queries Gemini uses when answering a prompt, by running it multiple times with Google Search grounding and reporting frequency distribution. Use when investigating AEO query patterns, understanding how AI models search the web for a topic, or studying the probabilistic nature of AI-triggered search queries.

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modbender/skill-library-mcp
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March 6, 2026 at 18:33
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name
aeo-prompt-frequency-analyzer
description
Analyze what search queries Gemini uses when answering a prompt, by running it multiple times with Google Search grounding and reporting frequency distribution. Use when investigating AEO query patterns, understanding how AI models search the web for a topic, or studying the probabilistic nature of AI-triggered search queries.
# Prompt Frequency Analyzer Run a prompt N times against Gemini with Google Search grounding enabled. Collect and report the frequency of search queries Gemini generates across all runs. ## Usage ```bash GEMINI_API_KEY=$(security find-generic-password -s "nano-banana-pro" -w) \ python3 scripts/analyze.py "your prompt here" [--runs 10] [--model gemini-2.5-pro] [--concurrency 5] [--output text|json] ``` Run from the skill directory. Resolve `scripts/analyze.py` relative to this SKILL.md. ## Options - `--runs N` — Number of times to run the prompt (default: 10) - `--model NAME` — Gemini model to use (default: gemini-2.5-pro) - `--concurrency N` — Max parallel API calls (default: 5; keep ≤5 to avoid rate limits) - `--output text|json` — Output format (default: text) ## Output Reports for each unique search query: - Frequency percentage (how many runs used that query) - Raw count - Top web sources referenced ## Notes - Gemini API key must be in `GEMINI_API_KEY` env var (stored in macOS Keychain under `nano-banana-pro`) - Each run is independent — Gemini may use different search queries each time - Retries failed requests up to 3 times with exponential backoff - Use `--output json` for programmatic consumption
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