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

Despite basic annotations (readOnlyHint: false, destructiveHint: false), the description adds critical behavioral context: invoke works even when the MCP is not installed, returns connect links for missing credentials, returns checkout/top-up links for unpaid tools, retries after user action, and requires workspace owner/admin for writes. This fully discloses side effects and permission needs.

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 every sentence adds meaningful guidance for a complex 14-action tool. It is front-loaded with the definition, uses a clear flow (search → describe → invoke), and packs nuances like install vs invoke, auth/payment links, and the prompt library without redundancy.

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 23 parameters, no output schema, and minimal annotations, the description is remarkably complete. It covers the main discovery and execution flow, one-off versus permanent usage, billing/auth behavior, permission requirements, installed-state flags, and the separate prompt library subsystem. Nothing important is left unaddressed.

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 coverage, the description carries the burden and does clarify the central `action` parameter (search, describe, invoke, install, subscribe, cancel, etc.) and the flow that connects `mcp_id`, `tool_id`, and `arguments`. However, many of the 23 fields (e.g., `limit`, `tier_slug`, `immediate`, `conversation`, `prompt_targets`, `report_context`) remain unexplained, so parameter semantics are only partially compensated.

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 definition: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then explains the core action flow (search → describe → invoke) and distinguishes itself from siblings by covering the prompt library. This is a specific, resource-bound purpose with clear scope.

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?

Provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use' versus 'Use install only to make an MCP PERMANENT.' It also tells the agent when to use request_mcp ('when nothing fits') and explains that search/describe discover, while invoke runs. This goes well beyond implied usage.

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