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

Beyond the annotations, the description discloses important runtime behavior: invoke works even when the MCP is not installed, credentials produce a connect link, empty wallet produces a checkout link, and write actions require workspace owner/admin. It also flags installed_in_toolkit vs installed_in_workspace. There is 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 and dense, but the length is justified for a complex multi-action tool with 14 action enum values. It is front-loaded with the core flow and key invoke behavior. A cleaner structure with bullets or separate sections would improve scannability, but every sentence contributes operational value.

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 absence of an output schema and the high complexity, the description covers the main return behaviors (profile from describe, connect/checkout links from invoke, shareable link from publish_prompt) and the auth model. Yet it omits explicit return/behavior details for some actions like search results, list_tools output, report_bug, and resume, so it is not fully complete.

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 0% schema description coverage, the description compensates by explaining the semantics of the main action field and the search/describe/invoke install flow, plus tool_id and arguments for invoking. It also explains prompt_* parameters and billing-related actions. However, it does not cover every parameter (e.g., resume, immediate, cancel_reason, conversation, report_context), leaving some gaps for a 23-parameter tool.

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 mcp.ai marketplace: a catalog of MCPs/tools plus a runtime for invoking them. It names the core flow (search → describe → invoke), covers capability requests, and distinguishes the prompt-library sub-feature. This goes well beyond the tool name and cannot be confused with siblings.

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 gives explicit usage direction: prefer invoke for occasional use, use install only for permanent toolkit additions, use list_tools for currently callable tools, and use request_mcp when nothing fits. It also clearly separates prompt-library actions from MCP actions. This is strong when-to-use guidance with named alternatives.

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