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

Beyond the annotations (which are minimal), the description discloses many behavioral traits: invoke works even when the MCP is not installed, it runs the tool one-off without adding to the toolkit, returns a connect link when credentials are needed, returns a checkout/top-up link when payment is required, and writes require workspace owner/admin. It also mentions that search/describe flag installed_in_toolkit vs installed_in_workspace, adding valuable context not inferable from annotations.

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 a long dense paragraph but packs a high density of relevant information. It is front-loaded with the core purpose and then systematically expands into the flow, exceptions, permissions, and prompt library. While it could be better structured with bullet points or shorter sentences, every sentence earns its place, and the length is justified by the tool's complexity.

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 description covers nearly all 14 actions in the schema, including search, describe, invoke, install, uninstall, subscribe, cancel, report_bug, request_mcp, list_tools, and the three prompt actions, plus edge cases for credentials, payments, and permissions. However, it omits discussion of the 'resume' action, the 'immediate' parameter, and 'tier_slug', which are present in the schema but not explained, leaving some gaps for a tool with this many parameters and no output schema.

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 23 parameters and 0% schema description coverage, the description must compensate. It does explain the meaning of key parameters through the workflow (action, query, mcp_id, tool_id, arguments) and describes the prompt-related actions (search_prompts, get_prompt, publish_prompt). However, it does not cover all parameters, such as tier_slug, immediate, resume, conversation, or cancel_reason, leaving some parameters unexplained beyond their names.

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 that the tool is the official mcp.ai marketplace—the in-platform catalog of MCPs/tools and the way to run them. It explicitly describes the core flow (search→describe→invoke) and distinguishes itself from sibling tools by covering capability requests, discovery, execution, and the prompt library. The verb 'catalog' and 'run' make the purpose unambiguous.

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 provides explicit usage guidance, such as 'prefer invoke for a single/occasional use; use install only to make an MCP PERMANENT' and explains when to use subscribe/cancel, report_bug, request_mcp, and the prompt library actions. It also clearly contrasts invoke vs install. However, it does not explicitly differentiate between the marketplace's report_bug action and the sibling report_bug tool, nor does it clarify when to use the sibling connect/authenticate tools instead of the connect links returned by invoke, leaving some potential ambiguity.

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