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.
Quellinformationen
- Repository
- modbender/skill-library-mcp
- Letzte Quellaktivität
- 6. März 2026 um 18:33
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 12
- Forks
- 3
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
SKILL.md wird angezeigt
SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- 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
Auf GitHub ansehen