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

The description adds significant value beyond annotations by detailing the full response structure (including fields like normalizedName, healthScore, etc.) and error handling. Annotations already mark it as read-only and open-world, and the description complements this without contradiction.

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 concise and well-structured: a clear purpose sentence, followed by parameter guidance, then the response and error structure. Every sentence provides necessary information 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 high schema coverage and a fully described output schema, the description is complete. It covers the tool's purpose, required parameters, response format, and error cases, leaving no ambiguity for the AI agent.

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 coverage is 100%, so the baseline is 3. The description adds the rationale for passing both parameters (because same-named tools can exist across products), providing additional meaning beyond the schema's basic descriptions.

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 verb 'Get' and the resource 'detailed information about a specific MCP tool', scoped to one product. It distinguishes from siblings by emphasizing that same-named tools across products are distinct, which is a key differentiator.

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 clear context on when to use the tool (when detailed info about a tool is needed) and emphasizes the need to pass both productSlug and tool name. However, it does not explicitly mention when not to use it or compare to sibling tools like tools.search or tools.find_for_task.

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