Scrunch CLI: A Brand Visibility Analysis Tool for the AI Search Era

Scrunch CLI is an open-source command-line tool that provides a full interface to the Scrunch AI API. It helps enterprises monitor brand visibility, analyze competitor performance, track user personas, and evaluate prompt effectiveness across AI search platforms like ChatGPT and Claude. This tool addresses the new challenges of AI-driven search behavior, enabling data-driven insights for generative engine optimization (GEO).

We are in an era of dramatic change in search behavior—more users now ask AI assistants like ChatGPT, Claude, or Perplexity instead of traditional search engines. This shift poses new challenges for businesses: How visible is your brand in AI responses? Are competitors mentioned more frequently? What types of questions lead users to your industry? Scrunch CLI was created to tackle these issues by integrating fragmented manual tracking into quantifiable data insights.

Developed by Adam Bertram, Scrunch CLI is a Python-based command-line tool that provides full API access to Scrunch AI (a SaaS for generative engine optimization). Its design focuses on enabling data analysts, marketers, and tech teams to efficiently perform brand monitoring, competitor analysis, and data export in a terminal environment. Built with Typer framework and Pydantic models, it supports JSON (for automation) and table (for human reading) outputs.

Scrunch CLI offers key modules:

1. Brand Management: Create/update brand profiles (name, website, themes) as core analysis units.
2. Competitor Tracking: Define competitors and compare their AI response presence, position, and sentiment.
3. Personas & Prompts: Simulate user groups (e.g., developers, marketers) and test prompts across AI platforms to track brand mentions.
4. AI Response Monitoring: Capture and analyze AI responses (tone, accuracy, brand position) with filters for platform, time, or persona.
5. Page Audits: Evaluate webpage content quality and AI search potential.
6. Agent Traffic Analysis: Identify non-human AI agent visits to websites.
7. Data Query: Aggregate metrics (response count, brand presence %) by date, platform, or persona for reporting.

Scrunch CLI is built with Python 3.9+ and relies on Typer, Pydantic, Requests, and python-dotenv. Installation: pip install -e .. Authentication uses API keys with multi-config support. A typical workflow:

1. Log in with scrunch auth login (configure API key).
2. Create a brand via scrunch brands create.
3. Define user personas with scrunch personas create.
4. Set test prompts using scrunch prompts create.
5. Fetch metrics with scrunch query metrics and responses with scrunch responses list.

Traditional SEO focuses on SERP rankings, but AI search delivers direct answers. Scrunch CLI addresses new optimization dimensions:

• AI Visibility: Frequency of brand mentions in AI responses.
• Position Advantage: Where the brand appears (start/middle/end) in answers.
• Sentiment: Positive/neutral/negative tone of AI descriptions.
• Competitor Comparison: Relative performance against rivals. This tool is becoming essential for businesses to stay competitive in AI-driven search.

Scrunch CLI is open-source under MIT license, allowing free use/modification. It reflects a modern SaaS trend: core platforms provide data/compute, while open-source tools enable programmatic access for automation and custom integration. For data-driven teams, it’s a flexible starting point to optimize brand performance in AI search—an increasingly core digital marketing capability.