Prepare a paid invocation of one live Agent Shop service. Returns the exact x402 HTTP request and price; it does not execute the service or bypass payment.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| inputs | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
With no annotations, the description carries the behavioral burden. It discloses that the tool returns 'the exact x402 HTTP request and price' and explicitly states it does not execute or bypass payment, which clarifies side effects. It does not address authentication, payment timing, or request expiration, leaving some gaps.
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 brief, front-loaded sentences deliver the core purpose and key clarifications with no filler. Every sentence 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?
The tool is relatively simple and has an output schema, and the description covers the core purpose and non-execution behavior. However, with 0% parameter coverage and no annotations, practical details such as how to obtain the slug, how the returned request should be used, and whether payment is captured remain unstated.
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 explain that 'slug' identifies the service or that 'inputs' contains the service arguments. The description only weakly implies a service context, so it does not compensate for the schema gap.
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 uses a specific verb ('Prepare') and resource ('paid invocation of one live Agent Shop service'), and clarifies that it does not execute the service. This makes the tool's purpose distinct from execution-oriented or read-only siblings.
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?
It provides context that the tool prepares rather than executes and does not bypass payment, but it never names alternatives like get_service, list_services, or market_service. The agent must infer when to use this tool versus its siblings.
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.
Each tool addresses a distinct action: shop services, market observations, and paid invocation. get_service and market_service could be confused by name alone, but their descriptions clearly separate the live shop catalogue from the observed market registry.
Most tools follow a clear get_/invoke_/list_ pattern, and market_* is used consistently for registry tools. Minor inconsistency: list_services uses plural while the getter tools use singular, and market_search is verb-first rather than object-first.
Five tools is a well-scoped set for an agent shop: listing, retrieving, invoking shop services, plus two market observation tools. Each tool earns its place without redundancy or bloat.
The core shop workflow is covered—discover, inspect, and prepare paid invocation—alongside market discovery and retrieval. Actual payment settlement and execution are intentionally out of scope, so there are no major dead ends for the stated purpose.