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aeo-baseline

Run configured prompts against Gemini with Google Search grounding and collect visibility signals into a JSON evidence file.

9|2|Updated Feb 12, 2026
Search Tags:#metrics#evidence#signals#grounding#gemini#baseline#visibility
One-click install
npx skills add https://github.com/psyduckler/aeo-skills --skill aeo-baseline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aeo-baseline
Source: https://github.com/psyduckler/aeo-skills/tree/main/aeo-baseline
Command: npx skills add https://github.com/psyduckler/aeo-skills --skill aeo-baseline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The AEO Baseline automates the measurement of a brand's visibility in AI answer engines by running configured prompts against Gemini with Google Search grounding, and it produces an append-only JSON evidence file conforming to the aeo-evidence-v1 schema.

Core Features & Use Cases

  • Atomic visibility baseline: runs multiple samples per prompt to extract signals (brand mentions, citations, positions, entities, sentiment, competitors) and computes Wilson 95% CI.
  • Produces an evidence JSON file consumable by aeo-report and aeo-optimize.
  • Works with a workspace config and can operate in ad-hoc mode for a one-shot snapshot.

Quick Start

Run the baseline script to measure a brand's visibility baseline with configured prompts.

Frequently Asked Questions about aeo-baseline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I measure my brand's visibility in AI answer engines?▼

To measure AI visibility, you can automate configured prompts against Gemini with Google Search grounding to collect brand mentions, citations, and competitor signals into a JSON evidence file.

What signals should I track to establish an AI visibility baseline?▼

An AI visibility baseline tracks brand mentions, citations, positions, entities, sentiment, and competitors across multiple prompt samples to compute a Wilson 95% confidence interval.

How do I monitor brand visibility changes over time using Gemini?▼

You monitor brand visibility changes by running recurring baseline measurements that append new signal collection results to an evidence file, tracking deviations from the initial baseline.

Do I need a Gemini API key to collect AI search grounding evidence?▼

Yes, collecting AI search grounding evidence requires a GEMINI_API_KEY in your environment, Python 3.9 or higher, and a workspace config or ad-hoc mode to execute the measurement script.

Can I generate a one-shot AI visibility snapshot without a full workspace config?▼

Yes, you can operate in ad-hoc mode to generate a one-shot visibility snapshot, running prompts against Gemini and writing results to the aeo-evidence-v1 schema without a persistent workspace config.

What format does the AI visibility evidence file use for reporting?▼

The AI visibility evidence file uses an append-only JSON format conforming to the aeo-evidence-v1 schema, making it directly consumable by downstream reporting and optimization workflows.

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