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

The description discloses important behavioral traits beyond annotations: writes require workspace owner/admin, invoke is a one-off execution that does NOT bloat the tool list, install makes the MCP permanent, and the prompt library allows sharing via a link that opens without login. It even explains failure paths (connect link, checkout link) and retry behavior, which is much richer than the annotation flags alone.

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 paragraph, but each section earns its place: core flow, KEY invoke behavior, install vs invoke, and the prompt library. It uses labels like 'Core flow:' and 'KEY:' to aid scanning. It could be tightened, but for a tool with 14 actions, the length is justified and it remains well-structured.

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 provides comprehensive context: it covers all action categories, auth constraints, failure modes, and even the prompt library. It explains the two major sub-domains (MCP execution and prompt retrieval) well enough for an agent to select actions and invoke parameters correctly. The absence of output schema is mitigated by describing what each action returns (profile, links, shareable URL).

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?

Although schema description coverage is 0%, the description compensates significantly by mapping actions to their parameter roles (e.g., action=search, mcp_id for describe, tool_id+arguments for invoke, prompt_slug for get_prompt). It does not explain every parameter (e.g., immediate, tier_slug, conversation), but the core action-specific parameters are contextualized. Given the large parameter count, the partial coverage is reasonable.

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?

Description clearly introduces the tool as the 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explains the core search → describe → invoke flow and covers actions like install, subscribe, and the prompt library, making the tool's broad scope understandable. It doesn't explicitly compare itself to siblings like authenticate/connect, but its marketplace identity is unambiguous and distinct.

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?

Usage guidance is explicit and prescriptive: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'. It also explains what happens when credentials are missing or wallet is empty, and tells the agent to retry after the user completes the connect/checkout. The description even distinguishes installed_in_toolkit vs installed_in_workspace, giving clear context for interpreting search results.

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