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anthesiallc

StoreSignal MCP Server

by anthesiallc

analyze_store

Analyze any Shopify store URL to get a complete profile including theme, apps, payment providers, revenue estimate, and industry classification.

Instructions

Analyze a single Shopify store URL and return a full structured profile.

Returns the store's name, theme, product count, apps installed, payment + analytics + checkout providers, CDN brand, security headers, schema.org markup, AI-classified industry / store type / growth stage (paid tiers), revenue estimate, social media, and more.

Use this as the default entry point when the user asks "what's this store using" or "tell me about https://...". If the URL is already in the 19K-store corpus the response is served from cache; otherwise the API runs a fresh crawl (5-15 seconds for new stores).

Args: url: Shopify store URL, e.g. "https://www.allbirds.com".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, but description discloses caching behavior for known stores and fresh crawl timing for new stores. Mentions paid tiers for some classification fields, though slightly ambiguous. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with main action first, then output list, usage guidance, caching behavior, and parameter description. Concise yet comprehensive with no unnecessary fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description lists many specific outputs and explains caching behavior, making the tool easy to understand. Given the complexity, it is very complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter 'url' with 0% schema description coverage. Description adds example URL and explains it's a Shopify store URL, providing meaningful guidance beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it analyzes a single Shopify store URL and returns a full structured profile, listing many specific outputs. It distinguishes itself from siblings like compare_stores and find_stores_using_app by being the default entry point.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this as the default entry point when the user asks...' providing clear when-to-use guidance. While it doesn't state when not to use, the context implies alternatives for specific queries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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