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

The description discloses crucial behavioral traits beyond the annotations: it states that writes require workspace owner/admin, explains that invoke works even when the MCP isn't installed, and details the connect/checkout link flow for authentication and payment. It also clarifies that install makes permanent changes. These details go well beyond the basic annotations (readOnlyHint: false, openWorldHint: true) and are consistent with them.

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 long, dense single block of text. It front-loads the purpose and core flow but packs extensive detail (permissions, link flows, prompt library) without clear sectioning. While every sentence carries information, the lack of formatting hurts scannability, and some repetition exists (e.g., restating 'mcp.ai' multiple times). It earns a middling score for density over conciseness.

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 and lack of an output schema, the description covers the key aspects: the core flow, the distinction between invoke and install, permission requirements, payment/authentication behaviors, and the prompt library. It explains what list_tools returns and what describe provides. It is fairly complete for a high-level overview, though some niche actions (resume, report_context) are not elaborated.

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 must compensate for parameter meanings. It does explain the high-level flow and maps some parameters (action, mcp_id, tool_id, arguments) to their roles in the search-describe-invoke pipeline. It also covers prompt library parameters like prompt_slug and prompt_body. However, many parameters (immediate, tier_slug, conversation, prompt_targets, cancel_reason, etc.) remain undocumented, leaving 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 states the tool's purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes itself from siblings by positioning itself as the central marketplace for discovering, describing, and invoking MCPs, while also covering the prompt library. This is a specific verb+resource with clear scope.

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 guidance on when to use the core actions: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT in the active toolkit.' It also explains the search-describe-invoke flow and mentions alternatives like list_tools. However, it does not explicitly address when to use this tool versus sibling tools like the standalone report_bug, leaving some potential ambiguity.

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