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

The description goes well beyond the sparse annotations: it discloses that invoke runs tools even without installation, that writes require workspace owner/admin, that paid tools may return a top-up link, and that search/describe flag installation state. No contradiction with the annotations exists.

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?

The description is dense but logically structured: primary purpose, core flow, key one-off invoke behavior, install-vs-invoke distinction, and the prompt library section. It is longer than ideal and includes a stray Portuguese example, but the length is largely justified given the tool has 14 actions and 23 parameters.

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 tool's complexity and the absence of an output schema, this description covers almost everything an agent needs: action semantics, return behaviors, authentication/credential links, payment top-up flow, permission requirements, and the distinction between one-off and permanent installation. It also explains the prompt library sub-system clearly enough for correct tool selection and invocation.

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?

With 0% schema description coverage, the description compensates by explaining the central action=search/describe/invoke flow, the role of tool_id and mcp_id, and prompt-related fields like prompt_body, prompt_vars, and prompt_slug. However, several parameters such as immediate, tier_slug, conversation, request_name, cancel_reason, and prompt_targets are only inferable from their names and are not explicitly documented.

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 identifies the tool as the mcp.ai marketplace catalog and execution layer, and immediately enumerates its two main purposes: discovering/running MCPs and hosting the prompt library. It differentiates itself from sibling tools by describing its core flow (search → describe → invoke) and covering capability requests such as "find an MCP that does X."

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 gives explicit usage guidance: prefer invoke for one-off use, use install only for permanent toolkit membership, use list_tools to see what is immediately callable, and use request_mcp when nothing fits. It also explains when invoke will return connect or checkout links and tells the agent to retry after the user completes the flow.

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