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

The description discloses important behaviors beyond annotations: invoke runs tools one-off even when not installed, credential/payment gaps return connect/checkout links, writes require workspace owner/admin, and prompt links open without login. These details add substantial context and do not contradict the 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, but it is dense and well-structured: it front-loads the core flow, then covers key edge cases, permissions, and the prompt library. A few clauses could be tightened, but the length is largely justified by the tool's multi-action complexity.

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 complex 23-parameter dispatcher with no output schema, the description is remarkably complete. It covers the search→describe→invoke flow, install vs invoke semantics, auth/billing behaviors, prompt-library usage, and fallback actions, leaving the agent well-equipped to select and invoke the correct action.

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 coverage, the description compensates by explaining the action parameter's enum values and the roles of mcp_id, tool_id, arguments, prompt_slug, and prompt_vars. It does not define every one of the 23 parameters, but the core flow and prompt-library sections give enough semantic grounding for most fields.

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 resource (the mcp.ai marketplace) and its dual role as a catalog and execution layer. It explicitly names the core actions (search, describe, invoke) and distinguishes the tool from siblings by framing it as the in-platform way to discover and run MCPs.

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: '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 directs users to request_mcp when nothing fits and separates the prompt-library actions from MCP actions.

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