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

The description goes beyond annotations by disclosing behavioral nuances: invoke runs one-off without adding to toolkit, requires auth via connect link or payment via checkout link, and has an implicit install behind it. It states permission requirements for writes (workspace owner/admin). It also clarifies that search/describe flag installed_in_toolkit vs installed_in_workspace. This adds substantial context beyond the annotations (readOnlyHint=false, openWorldHint=true, etc.) and contains no contradictions.

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 appropriately dense for the tool's complexity. It front-loads the purpose and core flow, then details key distinctions and lists actions. It uses dashes and semicolons to structure content, but remains a single paragraph. It could be broken into sections for readability, but every sentence adds value, and it is not padded with fluff.

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 23 parameters and no output schema, the description is largely complete: it explains all actions, the flow, auth/permission requirements, payment edge cases, and prompt library. It does not describe exact return formats, but it indicates outcomes (e.g., 'describe returns one MCP's full profile', 'invoke returns a connect link', 'publish_prompt returns a shareable link'). This is sufficient for an agent to select and invoke the tool 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 must compensate. It explains the role of key parameters such as action (with exhaustive enum list), mcp_id (used in describe), tool_id and arguments (invoke), and prompt_* params for the prompt library. However, it does not explicitly map every parameter (e.g., limit, query, immediate, tier_slug, prompt_vars, cancel_reason) to its role. It covers the main ones but leaves some ambiguity for less common actions. This is adequate for an agent to use the tool effectively, though not exhaustive.

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 states the tool's role: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It differentiates from siblings by covering marketplace functions, search, invoke, and prompt library, which none of the sibling tools (authenticate, connect, report_bug, show_version, toolkit_info, tribunal_trf6_processo_consultar) address. The core flow (search→describe→invoke) is explicitly outlined.

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' and 'Use install only to make an MCP PERMANENT in the active toolkit'. It also names alternatives for specific actions: 'subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP'. It clearly explains the conditions for invoke returning connect/checkout links and the need for retries, and notes that writes require workspace owner/admin.

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