Check the review status of a store you registered with register_store. Returns pending, approved, or rejected (with the reason). Once approved it also returns the ERC-8004 agent id and the per-seller MCP url.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The slug returned by register_store. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses the return states (pending, approved, rejected with reason) and additional data upon approval. It does not cover error behavior or side effects, but for a read-only status check it is fairly transparent.
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 unnecessary words. Information is front-loaded and every sentence adds value.
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?
Given the low complexity (one parameter, no output schema), the description provides sufficient information about what the tool does and returns. It is complete for its purpose.
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 coverage is 100% and already describes the slug parameter well. The description adds little new meaning beyond stating the slug is from register_store. Baseline 3 is appropriate.
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?
The description clearly states the tool checks the review status of a registered store, specifying the exact return values and additional details once approved. It is distinct from sibling tools like register_store or get_store_card.
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?
The description implicitly clarifies usage by connecting to register_store, indicating it should be used after registration. It does not explicitly mention when not to use or alternatives, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (discovery, purchasing, negotiation, seller management, taste/intent). Some overlap exists, e.g., multiple ways to get product details, but descriptions clarify distinct use cases. A few tools like find_buyers and get_buyer_briefs might be confused at first glance but have different inputs.
Tool names predominantly follow verb_noun pattern in snake_case, e.g., find_seller, buy_product, get_shipping_quote. The outlier is seller_mcp_url which starts with a noun instead of a verb, and negotiate is a bare verb but fits. Overall consistent with minor deviations.
28 tools is on the high side for a single server, but the domain is complex (agentic commerce covering discovery, purchasing, negotiation, seller registration, etc.). The count is borderline heavy but reasonable for the breadth of functionality.
The tool set covers major aspects of agentic commerce: search, buying, negotiation, shipping, digital delivery, seller onboarding, and taste/intent. Missing features like order tracking or store updates are minor gaps; core workflows are well-supported.
