Merchant verification for AI shopping agents.
Scored across 1 tool
Only one tool exists, so there is no possibility of confusion or overlap with other tools.
With a single tool, naming is trivially consistent. The name 'verify_store' follows a clear verb_noun pattern.
A single tool feels thin for a registry service, even if it's focused on verification. The scope is limited, but the tool count is borderline rather than extreme.
The server only provides a verification tool, lacking essential CRUD operations (create, update, delete, list) expected for a registry, leaving significant gaps.
Verify whether a merchant has an active GenGEO verification record. Results should be treated as one signal within a broader agent decision framework.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavioral traits such as idempotency, error handling, or whether it is read-only. The description merely states the verification, leaving the agent uninformed about side effects or limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence states purpose, second adds usage context. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with one required param and no output schema. Description covers the verification purpose but omits details on return value format or error conditions, which would be expected given no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the 'domain' parameter at all. It adds no meaning beyond the schema, failing to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool verifies whether a merchant has an active GenGEO verification record, with a specific verb and resource. No siblings exist, so distinction is not needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states results should be treated as one signal within a broader framework, guiding the agent on how to use the output. No mention of when not to use, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
verify_storeNeutral verified-merchant index for AI shopping agents; regulated/alcohol-first; earned-trust only.
AI-agent product catalog: search, lookup & purchase routing over verified merchant data.
Shopify product discovery and x402-paid offer verification for AI agents.
Open, verified shop database for AI agents: products, offers, price comparison, trust and coupons.
Add one secure layer between your agents and this server.