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

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description discloses key behaviors: invoke works one-off without installation, credential needs return a connect link, paid-and-wallet-empty returns a checkout/top-up link, and writes require workspace owner/admin. It also explains the search/describe installed_in_toolkit vs installed_in_workspace flags. No contradictions 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 a single dense paragraph but is well-structured: it starts with the core flow, uses 'KEY:' to highlight the most important behavior, then covers permissions and the prompt library. Every sentence adds value, though at ~200 words it is long; the complexity of the tool justifies the length.

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 params and many actions, the description covers the major workflows end-to-end: discovery, profiling, one-off execution, permanent install, billing/auth behavior, permissions, and prompt library. It omits specifics like pagination (limit) and return value formats, but given no output schema, it provides enough context for an agent to handle the primary use cases correctly.

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 coverage is 0%, so the description carries the burden. It explains the 'action' parameter values contextually, mentions mcp_id/tool_id/arguments implicitly in the flow, and describes prompt_vars as {{variables}}. However, many parameters (limit, query, message, immediate, tier_slug, cancel_reason, etc.) remain unexplained, leaving gaps for an agent trying to construct precise calls.

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 a clear verb+resource statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates the core flow (search → describe → invoke) and the prompt library, distinguishing this from sibling tools by covering cataloging, execution, and prompt management in one place.

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 when-to-use guidance: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and 'list_tools lists what is callable right now.' It also explains when to use request_mcp ('when nothing fits') and gives the full action flow, leaving little ambiguity about selecting this tool.

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