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

Annotations are minimal (only readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false), so the description carries the burden and delivers richly: it discloses that 'invoke runs the tool pontualmente (one-off) without adding the MCP to the toolkit', the connect-link and checkout/top-up fallback flows for auth/payment, and that 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.' No contradiction with annotations — readOnlyHint=false is consistent with the documented write operations.

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 enormous wall of text. It is front-loaded with the core purpose (good), but then crams the action semantics, invoke behavior, auth/payment flows, permission requirements, and the entire prompt library into one dense unwieldy paragraph with no section breaks or scannable structure. For an agent parsing under time pressure, this forces a full read of ~250 words to extract the decision logic.

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 a very high complexity tool (14 actions, 23 params, no output schema), the description covers the critical decision points well: which action to pick, install vs invoke, write-permission requirements, and auth/payment fallbacks. But it leaves many parameters undocumented, and with no output schema it never describes return shapes (e.g., what search results look like, what invoke returns on success vs needing a connect link) — the behavioral hooks are there but results are not.

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 description coverage is 0% across 23 parameters, so the description must compensate. It explains the action enum meaningfully (search, describe, invoke, install, list_tools, etc.) and references tool_id, mcp_id, and arguments implicitly via the flow. But 17+ parameters (limit, query, message, immediate, tier_slug, prompt_body, prompt_vars, conversation, prompt_title, request_name, cancel_reason, cancel_comment, prompt_targets, report_context, prompt_category, request_details, prompt_description) receive no semantic explanation at all, leaving agents to guess formats and meaning.

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 opening states a clear scope: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It gives a specific verb+resource+scope and distinguishes itself from siblings (authenticate, connect, show_version, etc.). However, the tool is overloaded with 14 distinct actions across MCP operations AND a prompt library, making the true purpose diffuse and sprawling.

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?

Strong internal guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT in the active toolkit', 'list_tools lists what is callable right now', and the core search→describe→invoke flow is articulated. But it never contrasts against sibling alternatives — notably the marketplace's own report_bug action vs the sibling report_bug tool, and no 'when NOT to use marketplace' guidance.

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