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

The description goes well beyond the annotations by explaining critical behaviors: invoke runs tools even when not installed, returns connect/checkout links for auth/payment, and writes require workspace owner/admin. It also notes the distinction between installed_in_toolkit vs installed_in_workspace, adding valuable context that the annotations do not provide.

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 and information-rich, but it is a single block of text that could be more scannable with bullet points or separation of the marketplace flow from the prompt library. Nevertheless, every sentence adds meaningful detail, 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?

Given the tool's complexity (14 actions, 23 parameters, no output schema), the description is remarkably complete. It covers the core flow, auth requirements, error handling (connect/checkout links), installed status flags, and even introduces the prompt library. This provides enough context for an agent to correctly select and invoke the appropriate action in most scenarios.

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?

The description compensates for the 0% schema coverage by explaining the main action values and their purposes, which directly informs how to use related parameters. However, it does not address every parameter explicitly (e.g., immediate, tier_slug, cancel_reason, conversation), relying on self-explanatory names or inferred context. Given the large parameter count, more detail would be beneficial, but the action-based guidance is already strong.

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 official mcp.ai marketplace, serving both as a catalog of MCPs/tools and a way to run them. It provides a concrete action-oriented overview (search, describe, invoke) and distinguishes itself from sibling tools by describing its scope and core flow, making its purpose unmistakable.

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 guidance on when to use invoke vs. install, stating 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also clarifies the roles of list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library actions, giving clear context for choosing among alternatives within this tool.

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