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Ecommerce Leads

Look up a store

lookupStore
Read-only

Look up one ecommerce store by domain. The reply has company data, estimated revenue, marketing budget, traffic, Google and Meta ad spend, ad counts, a Conversion Rate Score, buying signals, the store phone number, and social and ad-library links. Decision-maker contact fields are not in the fields list. With OAuth access, the decisionMakers object shows the contacts that you revealed. When other active stores use the same base domain, the reply has sharedMetrics. Those stores show the same traffic and ad numbers, because the data belongs to the base domain. Limits: anonymous access, 20 lookups per hour per IP. OAuth access, 20 lookups per minute, and the call writes a lookup history row.

Input Schema

NameRequiredDescriptionDefault
domainYesThe store domain, for example example.com. A full URL also works.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior1/5

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

The description discloses useful behavior, including rate limits and sharedMetrics behavior for stores on the same base domain. But it also says OAuth calls 'write a lookup history row,' which contradicts the readOnlyHint=true annotation.

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

Conciseness4/5

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

The purpose is front-loaded and the description is dense with relevant response, access, and limit details. It is longer than strictly necessary, but most of the information earns its place.

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?

There is no output schema, so the description carries the burden of explaining return values, and it does so thoroughly: company data, ad metrics, decisionMakers, sharedMetrics, and links. It also covers rate limits and access differences, making it complete enough for an agent to call correctly.

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

Parameters3/5

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

Schema description coverage is 100%, and the schema already explains that 'domain' accepts a domain such as example.com or a full URL. The description adds useful context about base-domain grouping, but it does not add much meaning about the parameter 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?

The description states a specific verb and resource: 'Look up one ecommerce store by domain.' That scope clearly distinguishes this single-store lookup from sibling tools such as searchStores and getStoreChart.

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

Usage Guidelines3/5

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

The description makes clear that this is for looking up one store by domain and explains anonymous versus OAuth limits. However, it does not explicitly name searchStores or other alternatives, nor does it state when not to use this tool.

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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