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

Annotations only provide flags (readOnlyHint=false, openWorldHint=true) — the description carries substantial burden and exceeds it: it discloses that invoke runs one-off without bloating the toolkit, returns connect links for credentials and checkout/top-up links for empty wallets (then retry), requires workspace owner/admin for writes, and explains the prompt library's openable-without-login links. No contradiction with annotations; the content meaningfully supplements the flag-only annotation set.

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 dense, single-paragraph wall of text with run-on sentences, mixes Portuguese ('pontualmente'), and front-loads the core flow but buries the prompt-library section at the end without structural separation. Despite being information-rich, its lack of breaks or emphasis makes it hard to scan — the highest-value distinction (the four action sub-flows) is not visually or rhetorically isolated.

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 the very high complexity (14 actions, 23 params, no output schema), the description covers a remarkable breadth: discovery flow, one-off vs permanent install semantics, billing/auth edge cases, permission requirements, and the separate prompt-library feature. Nearly all behavioral aspects an agent needs are present. The only deduction is structural — completeness of content is high, but the unorganized form risks the agent missing key clauses buried mid-paragraph.

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%, so the description must compensate for 23 undocumented parameters. The prose maps the core flow to the central params (action, mcp_id, tool_id, arguments, immediate, tier_slug) and lightly touches cancel_reason and prompt_* params, but leaves many (conversation, request_name, report_context, prompt_targets, request_details, prompt_category) unexplained. Partial compensation — the most important parametrization is clear, but the long tail is unaddressed.

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 mcp.ai marketplace — a discovery, execution, and management hub dispatching via the `action` parameter across search/describe/invoke/install/billing/prompt-library actions. It distinguishes itself from siblings (authenticate, connect, show_version) by framing itself as the in-platform catalog and execution path. However, the enormous scope (14 actions in one tool) makes the single-sentence purpose less crisp than a single-responsibility 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?

The description gives explicit when-to-use guidance: 'Use install only to make an MCP PERMANENT in the active toolkit', 'prefer invoke for a single/occasional use', and documents the core flow (search → describe → invoke). It also names alternatives (list_tools for what is currently callable, request_mcp to build a NEW MCP). This is textbook-level usage direction.

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