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

Beyond the sparse annotations, the description discloses that invoke works for uninstalled MCPs as a one-off without bloating the toolkit, returns auth/checkout links requiring retry after user action, and that writes need workspace owner/admin. It also details the prompt library's shareable links that open without login, with no contradiction to 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 front-loaded with the core purpose but is a dense, single-paragraph wall of text covering 14 actions, invoke behavior, permissions, and the prompt library. The content is valuable and each sentence adds information, but the unstructured format sacrifices conciseness and scanability.

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 breadth (14 actions, 23 optional parameters, no output schema) the description comprehensively covers high-level flows, auth, payment, one-off execution, permissions, and prompt publishing. It lacks return-value details and parameter-level specifics, but provides enough operational context for an agent to select actions and handle connect/checkout links.

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 but only does so partially. It explains action, tool_id, arguments, and prompt-related parameters like prompt_vars and prompt_slug, but leaves many meaningful parameters (limit, immediate, tier_slug, conversation, prompt_targets, cancellation fields, report_context) entirely implicit or unexplained.

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 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which clearly states the tool's resource and function. It enumerates the core search→describe→invoke flow and distinguishes sub-actions like report_bug, request_mcp, and search_prompts, separating it from sibling tools.

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 decision guidance: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use' and explains when invoke returns a connect link or checkout link. It also specifies when to use list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library actions, plus ownership requirements for writes.

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