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

Annotations indicate openWorldHint=true and readOnlyHint=false, but the description adds rich behavioral context: invoke runs tools without installation, may return connect/checkout links for auth/payment, writes require workspace owner/admin, and actions like install/uninstall/subscribe/cancel have side effects. This goes well beyond the sparse annotations, providing transparency about permissions, execution model, and failure paths.

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 single long paragraph (~300 words) but is densely packed with essential information, including a clear flow (search→describe→invoke) and key distinctions (invoke vs install). It is front-loaded with the core flow and emphasizes the most critical insight (invoke works without installation). While not broken into sections, it efficiently covers all functionality without wasted words. The length is justified by the fourteen actions plus prompt library.

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 (23 parameters, 14 actions, no output schema), the description is remarkably complete. It covers the core interaction model, permission requirements, failure handling (connect/checkout links), distinctions between installed_in_toolkit and installed_in_workspace, and the prompt library. It explains all major behaviors and what to expect, making it sufficient for an agent to use the tool effectively across its many modes.

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 any of the 23 parameters directly. While it mentions actions (e.g., 'action=search'), it never maps specific parameters like 'query', 'mcp_id', 'tool_id', or 'arguments' to their roles. The description focuses on the tool's purpose and flow rather than parameter usage, leaving an agent to infer which fields to populate for each action. This is a significant gap given the tool's complexity.

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 this is the official mcp.ai marketplace, acting as both catalog and runner for MCPs. It explains the core flow (search→describe→invoke) and distinguishes itself from siblings like authenticate, connect, and toolkit_info by focusing on marketplace-specific actions. The verb 'marketplace' is a noun but the description thoroughly defines its role, making 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?

Explicit guidance is provided: use search to discover, describe to inspect, invoke for one-off runs, install only for permanent additions, and list_tools to see current callables. It clearly contrasts invoke vs install and covers the prompt library separately. This gives an agent clear decision rules for when to use each action, meeting the dimension fully.

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