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 runs one-off without installing, returns connect/checkout links on missing credentials or empty wallet, and writes require owner/admin permissions. It also explains installed_in_toolkit vs installed_in_workspace flags, adding significant context.

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 structured, starting with the overall purpose, then the core flow, key behaviors, usage guidance, and prompt library. Each sentence adds value, though the phrase 'pontualmente' is awkward and the text could be tightened without losing information.

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 tool with no output schema, the description covers the main flows: discovery, execution, installation, billing, reporting, and prompts. It omits specifics on return formats and some parameter semantics, but overall it gives a robust operational picture.

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 carries the full burden for 23 parameters. It explains the core action values (search, describe, invoke, install), tool_id, mcp_id, arguments, and prompt-related parameters, providing meaning beyond the schema. It omits details for some params like limit, immediate, and cancel_reason, but it covers the most operationally important ones.

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 tool as the official mcp.ai marketplace, both a catalog and an execution layer for MCPs/tools. It uses a concrete verb-resource structure and lays out the core flow (search → describe → invoke), which distinguishes it from sibling tools like authenticate 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 provides explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use'), when to use subscribe/cancel, report_bug, request_mcp, and the prompt library functions. It also states that writes require workspace owner/admin, giving clear operational constraints.

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