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

The description reveals critical behavioral traits beyond the annotations: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente... without adding the MCP to the toolkit.' It also discloses side effects and permissions: 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.' It even explains conditional response behaviors like returning a connect link or a checkout/top-up link. No contradiction with 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 long but each sentence earns its place for a tool with 14 actions and 23 parameters. It is front-loaded with the main purpose, then progresses logically from core flow to edge cases, permissions, and the prompt library. It avoids redundancy and maintains a coherent structure despite the density.

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 params, no output schema), the description is remarkably complete. It explains the full lifecycle from search to invoke, covers auth and payment interruptions, distinguishes permanent install from one-off invoke, lists list_tools as a status check, and fully covers the prompt library sub-feature. It omits no major behavioral outcome and provides enough context for an agent to invoke any action correctly.

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 schema description coverage at 0%, the description carries the burden of explaining parameters. It successfully adds meaning for the most critical ones: action values ('search', 'describe', 'invoke', 'install', etc.), tool_id selection ('so you pick the right tool_id'), and arguments (implicitly via 'invoke RUNS that tool'). However, it leaves many parameters unexplained (limit, immediate, tier_slug, cancel_reason, etc.), relying on their names for inference. Still, the workflow-level guidance is substantial enough to offset the lack, so this is above baseline but not perfect.

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 opens with a clear, specific purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes this tool from siblings by establishing it as the central catalog and execution hub, and it further enumerates the two primary capability areas (MCP discovery/invocation and the prompt library).

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 when-to-use guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... so you pick the right tool_id → invoke RUNS that tool.' It also gives direct preference rules: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' This is superior, actionable context for choosing among the 14 actions.

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