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

The description discloses key behavioral traits beyond annotations: invoke works even when the MCP is not installed, it runs one-off without adding to the toolkit, writes require workspace owner/admin, subscribe/cancel handle per-MCP billing, and search/describe include installed_in_toolkit vs installed_in_workspace flags. It also explains what invoke returns for auth and payment cases. The text does not contradict the annotations (readOnlyHint=false, openWorldHint=true).

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 densely informative and well-structured: it opens with the umbrella purpose, then uses 'Core flow', 'KEY', 'Use install only', and 'It also carries' to organize major behavior and alternatives. Every sentence contributes meaningful information—edge cases, permissions, or workflow distinctions—so the length is justified rather than bloated.

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 very complex multi-action tool with 23 params and no output schema, the description is unusually complete: it explains the main workflows, the key invoke edge cases, install-vs-invoke trade-offs, admin requirements, and the prompt library. It does omit a few behaviors (e.g., resume, immediate, tier_slug semantics) and does not describe output shapes, but overall it gives an agent enough context to navigate the tool safely and effectively.

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 23 parameters and 0% schema description coverage, the description carries heavy responsibility. It adds semantic context for the key parameters (action, mcp_id, tool_id, arguments, prompt_title, prompt_body, prompt_vars, request_name, request_details, cancel_reason/comment) by explaining the core flows. However, several parameters remain unexplained in both schema and description (e.g., immediate, tier_slug, conversation, message, limit, report_context), so it does not fully compensate for the coverage gap.

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 clear purpose: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes itself from siblings by enumerating its own action categories (search, describe, invoke, install, subscribe, prompt library) and explicitly contrasting invoke vs install, making its scope unmistakable even alongside tools like authenticate and connect.

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: 'prefer invoke for a single/occasional use' versus 'Use install only to make an MCP PERMANENT in the active toolkit.' It also handles edge cases (credential/login returns a connect link; empty wallet returns checkout link), calls out admin permission requirements for writes, and suggests request_mcp when nothing fits. This is strong decision-making support beyond a bare verb+resource statement.

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