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

Annotations provide only readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false; the description carries most of the burden and delivers. It discloses side effects and retry semantics ('invoke returns a connect link' for auth, 'a checkout/top-up link' for empty wallet, 'the user opens it, then you retry'), scoping ('runs the tool pontualmente... without bloating the tool list'), and permission requirements ('Writes... require workspace owner/admin'). Minor gap: uninstall's destructive effect is named in the permissions sentence but not explained. No contradiction 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 ~350-word run-on paragraph — dense and front-loaded well (purpose → flow → key exception → permissions → prompt library), but no bullets, headers, or separation between the MCP-catalog and prompt-library concerns. Given 14 dispatch actions, some length is justified, yet restructuring would materially improve scannability. Every sentence earns its place, but the wall-of-text format costs it a higher score.

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 parameters, zero output schema, sparse annotations, and 14 dispatch actions spanning catalog discovery, execution, installation, billing, and a prompt library, this description is remarkably complete. It covers the discovery pipeline, one-off vs permanent execution, auth and payment fallbacks, owner/admin permission gates, installed-status flags, and each action's role. The only residue is a handful of underwritten parameters and no return-format details, but given the inherent complexity, this is near-ceiling completeness.

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 description coverage across 23 parameters, the description must compensate heavily. It maps most actions to their key inputs (action=invoke takes tool_id + arguments, publish_prompt uses prompt_body to return a shareable slug, search takes query, cancel takes cancel_reason, report_bug takes report_context, request_mcp takes request_name/details). However, several parameters remain unexplained: limit, immediate, conversation, message, and tier_slug are never addressed despite being significant to the search/subscribe flows.

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 precise identity: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates the full action dispatcher (search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt-library trio). The scope is unambiguously differentiated from siblings like authenticate, connect, and toolkit_info — this is the discovery/running/billing gateway, not an auth or system-info tool.

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?

Exceptionally explicit when-to-use guidance. It defines the canonical flow ('action=search discovers MCPs by intent → describe returns one MCP's full profile... so you pick the right tool_id → invoke RUNS that tool'), gives concrete query examples ('consulta um CPF', 'is there a tool for Y'), and draws a clear line between invoke (one-off, no toolkit bloat) vs install (permanent). It also separates the prompt library ('about ready-made prompt TEXT rather than MCPs') from the MCP catalog, and names list_tools, subscribe/cancel, report_bug, and request_mcp with their distinct triggers.

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