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

The description discloses behaviors beyond the minimal annotations (readOnlyHint=false, openWorldHint=true). It explains that 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit,' and details failure modes: 'if the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link.' It also states permission requirements: 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.' This goes far beyond the structured 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 dense and front-loads the core flow ('Core flow:'), but it crams many clauses into a long paragraph. It uses all-caps emphasis ('KEY', 'PERMANENT') which aids readability. While every sentence adds value, the structure could be improved with lists or separation between MCP and prompt-library sections. It is not wasteful but slightly overloaded.

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 params, no output schema), the description covers the core actions well: invoking, installing, subscribing, and the prompt library. It mentions 'subscribe/cancel handle per-MCP billing' but does not address the 'resume' action or parameters like 'immediate', 'conversation', 'cancel_reason', etc. It is comprehensive for main flows but lacks detail for less-common actions and edge cases, leaving an agent to guess parameter usage for some actions.

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 coverage is 0% and the description does not directly explain individual parameters. However, it adds meaning to the 'action' enum by describing each action's purpose (search, describe, invoke, install, etc.) and references mcp_id/tool_id/arguments implicitly in the flow. But the many prompt_* and request_* parameters remain unexplained. The description provides high-level semantics but does not fully compensate for the lack of per-parameter documentation across 23 params.

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 the tool's role as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It lists concrete capabilities (search, describe, invoke) and distinguishes the marketplace from sibling tools like authenticate or connect by covering both catalog and execution. The verb+resource structure is specific and non-tautological.

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?

Usage guidance is explicit and actionable: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... invoke RUNS that tool.' It also compares actions directly: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' It distinguishes the prompt library ('It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs'). This gives clear when-to-use and when-not-to-use guidance.

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