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

The description adds significant behavioral context beyond annotations: invoke works even when MCP is not installed and runs one-off without bloating the toolkit; if credentials needed, invoke returns a connect link; if paid with empty wallet, returns checkout/top-up link and then retry. It also mentions installed_in_toolkit vs installed_in_workspace flags and permission requirements for writes. 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 long (200+ words) but dense with useful information. It follows a logical structure: core flow, exceptions (invoke without install, links), permission requirements, and prompt library. Every sentence adds value, though it could be broken into bullets for easier parsing. It is not overly verbose for the tool's complexity.

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 tool's complexity (14 actions, 23 params, two functional areas), the description is remarkably complete. It covers the core flow, edge cases (credentials, payment, not installed), permission scope, prompt library (search/get/publish with shareable links), and differentiates install vs invoke. It does not detail every action (like resume or cancel_reason), but the essentials are covered. Excellent for such a broad tool.

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 must compensate. It explains the core parameters (action, mcp_id, tool_id, arguments) via the core flow, and mentions prompt-related params indirectly. However, it does not detail individual parameters like limit, query, immediate, tier_slug, cancel_reason, or prompt_vars. It provides high-level semantics for the main actions but not per-parameter detail, which is a moderate 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 clearly states the tool's role as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explicitly covers capability requests like 'find an MCP that does X'. It also distinguishes from siblings by mentioning the prompt library and the core flow (search → describe → invoke). This is a specific verb+resource with clear scope and differentiation.

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 when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', when to use list_tools, subscribe/cancel, report_bug, and request_mcp. It also explains the retry flow for connect/checkout links and states that writes require owner/admin. This is exemplary usage differentiation.

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