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

Annotations already declare readOnlyHint=true, so the agent knows the tool is safe and non-mutating. The description adds value by disclosing what the tool returns: 'when to use it, what it refuses, a working example, effective access limits, important outputs, provenance fields, recommended next calls, and the shared natural-language-to-strict-JSON interaction contract.' This gives a detailed picture of the tool's output behavior without contradicting the annotations. It doesn't mention potential errors (e.g., unknown tool name), but that's a minor gap.

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 three sentences and front-loaded with purpose. The second sentence lists important output categories – a bit long but every item adds value. The final sentence gives a clear call-to-action. No fluff, but the list is dense. It earns its length and does not waste the reader's attention.

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?

With no output schema, the description must explain return values, and it does by enumerating the content types. It also covers the discovery workflow and when to use the tool. It doesn't describe error behavior for invalid tool names, but given the low parameter count and simple purpose, the description is sufficiently complete for an agent to invoke the tool 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?

Schema description coverage is 100% – the only parameter 'tool_name' is described as 'Exact tool name from tools/list.' The description reinforces this by saying 'Use tools/list to discover names,' providing a helpful hint about the parameter's source. However, it adds no format, validation, or default information beyond what the schema already provides. The baseline of 3 applies because the schema fully documents the parameter.

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 function: 'Free blind-caller guidance for one tool visible on this MCP facade.' It uses a specific verb ('returns') and identifies the resource ('one tool'). It also lists concrete deliverables, distinguishing it from sibling tools that retrieve data (e.g., get_catalog, query_dataset). The purpose is unambiguous and front-loaded.

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 workflow: 'Use tools/list to discover names, then call this before an unfamiliar tool.' This tells the agent when to use the tool and gives a clear prerequisite step. It does not explicitly state when not to use it, but the guidance is strong enough for an AI agent to select it appropriately. The mention of 'before an unfamiliar tool' signals a clear use case.

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