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

This description adds major behavioral detail not present in the sparse annotations: invoke can run an uninstalled MCP one-off without bloating the toolkit, returns connect or checkout links in credential/payment gaps, requires owner/admin for writes, and distinguishes installed_in_toolkit versus installed_in_workspace. It aligns with the annotations and no contradiction is present.

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 and dense but for a large multi-action dispatcher, almost every sentence has a distinct purpose. It is organized starting with the core flow, then key behavioral caveats, permissions, and the prompt library. It would be stronger with clear bullets or explicit action→parameter mappings, but it is still effective.

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 complexity and lack of an output schema, the description covers the most important workflows, side effects, auth requirements, payment edge cases, and prompt-library behavior. However, it is not fully complete: actions like resume, uninstall details, exact return shapes for search/list/describe, and some per-action parameters are not spelled out.

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 needed to explain a lot. It meaningfully explains action, tool_id, arguments, prompt variables, and the overall request flow, but many parameters remain under-specified: limit, mcp_id, immediate, conversation, conversation tier, cancel_reason, request_details, report_context, and others are only names or implied. This leaves the agent with significant inference still required.

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 marketplace as the mcp.ai catalog and execution layer, listing the core actions (search, describe, invoke, install) and the prompt-library side. It is specific about the resource it manages and the capabilities it exposes, and it is distinguishable from sibling tools like authenticate, connect, and toolkit_info.

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 an explicit core flow (search → describe → invoke), states when to prefer invoke over install, and covers payments, credentials, and admin permissions. It also tells the agent which family of actions to use for prompts, subscriptions/cancels, and new MCP requests, so usage context is strongly specified.

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