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

Beyond the minimal annotations, the description discloses key behaviors: invoke works without installation, credential/payment failures return connect/checkout links, and writes require owner/admin. It also explains installed_in_toolkit vs installed_in_workspace flags. This is rich behavioral context that helps an agent anticipate outcomes.

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 highly structured, using explicit markers like 'Core flow:', 'KEY:', and a natural segregation of the marketplace and prompt-library features. Every sentence adds operational detail; there is no filler or repetition, and the most important information is front-loaded.

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, no output schema, and high complexity, the description covers all principal workflows, edge cases (connect/checkout links), permission requirements, and the separate prompt library. It even notes status flags and one-off vs permanent installation, making it complete enough to drive correct selection and invocation.

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 compensates well for the central `action` parameter by explaining each action's purpose. It also gives meaning to `mcp_id`, `tool_id`, and `arguments` through the invoke flow. However, many auxiliary parameters (e.g., `limit`, `query`, `prompt_title`, `cancel_reason`) are not described, leaving some guesswork for less common actions.

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 statement of purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then details the core search→describe→invoke flow, making the tool's role unmistakable. It also distinguishes the prompt-library sub-feature, so the full scope is explicit.

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 explicitly maps actions to use cases: search to discover, describe to inspect, invoke for one-off runs, install only for permanent additions, and list_tools for currently callable tools. It provides decision rules like 'prefer invoke for a single/occasional use' and states that write operations require owner/admin permissions.

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