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

Annotations only say readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds crucial behavioral context: invoke runs one-off without installing or bloating the toolkit, install makes permanent, auth failures produce connect links, unpaid tools produce checkout links, and writes like install/uninstall/subscribe/cancel require workspace owner/admin. This goes well beyond the annotations and outlines real-world side effects and prerequisites.

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 information-dense; every sentence contributes to explaining a different action or behavior (flow, install vs invoke, auth, billing, prompt library). The core flow is front-loaded and uses arrows for clarity, though it is a single continuous paragraph that could benefit from bullet points or section breaks to aid scanning.

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?

For a tool with 23 parameters, 14 enum actions, no output schema, and minimal annotations, the description is remarkably complete: it covers auth requirements, paid vs free behavior, permanent vs one-off installation, installed flags, prompt sharing, and when to use request_mcp. The main gaps are lack of per-action parameter mappings and any description of success return payloads, but the operational context needed to invoke correctly is largely present.

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 description coverage is 0% across 23 parameters, so the description must compensate. It explains the 'action' enum in depth and clarifies core parameters like tool_id ('pick the right tool_id → invoke RUNS that tool') and prompt-related fields. However, many parameters such as limit, query, arguments, immediate, tier_slug, cancel_reason, report_context, and prompt_targets are not explicitly tied to their actions, leaving the agent to rely on names alone.

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 immediately defines the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', giving a clear, specific mission. It further enumerates the core actions (search, describe, invoke, install, list_tools, etc.) and even hints at scope boundaries (prompt library vs MCP catalog), making it easy to distinguish from sibling tools like report_bug or toolkit_info.

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 when-to-use guidance: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use' and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also explains the core flow and how invoke differs from install, plus when credential or payment links appear, which directs the agent's decision-making beyond just what the tool does.

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