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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the analysis dimensions and that output is ranked by priority, but says nothing about the evaluation method, data sources, or limits of the open-world lookup.

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?

One dense sentence with zero waste, front-loading the core question ('why an agent may or may not select a merchant') before the deliverable and its dimensions.

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?

An output schema exists, so return values need not be explained, but the definition leaves the input format for 'merchant' ambiguous, which is a real hurdle for a diagnostic that presumably keys off a specific merchant identifier.

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 0% and the single 'merchant' parameter is an undifferentiated string. The description does not state whether this should be a domain, merchant name, or ID, so it fails to compensate for the schema gap.

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 uses specific verbs ('explain', 'return prioritized improvements') against a clear resource (a merchant's selection by an AI purchasing agent) and enumerates the five analysis axes. It does not name or differentiate itself from the closest sibling, merchant_agent_profile, leaving the agent to infer the boundary.

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 phrasing 'why an AI purchasing agent may or may not select a merchant' implies the diagnostic use case, but there is no explicit when-to-use, no prerequisites, and no reference to alternatives such as merchant_agent_profile or merchant_offer_search.

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