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

The description adds substantial context beyond the annotations: it declares the tool free, discloses that queries are recorded privately to improve articles (which explains the readOnlyHint=false side effect of logging), and sets output-handling rules about citing sources and not inventing answers. It does not mention authentication or rate limits, so it stops short of full behavioral disclosure.

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?

Three sentences, front-loaded with the cost and capability, then usage constraints, then output rules. The middle topic list ('pricing, terms, licensing, manufacturer rights, policies, Enterprise, delivery and account support') is a dense enumeration that could be trimmed, but the rest earns its place.

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 no explanation, and the annotations plus the logging disclosure cover the behavioral profile. The one material omission is the report_gap flag for flagging unanswered questions, which is central to the described escalation workflow but only implied by 'escalate unanswered parts to support'.

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%, so both parameters are already documented in structured data. The description reinforces the query constraints ('one question at a time', no personal information or full emails) but never mentions the report_gap parameter, so it adds little new meaning over the schema.

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 states a specific verb and resource (find source-linked answers) and enumerates the covered topic domains: pricing, terms, licensing, manufacturer rights, policies, Enterprise, delivery and account support. It is clear what the tool does, but it does not differentiate itself from the sibling get_pricing, which overlaps directly with the 'pricing' topic it claims.

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?

Usage context is implied rather than spelled out: 'Suitable for drafting replies to customer questions' and 'Submit one question at a time' guide the agent, and escalation of unanswered parts is named. However, no when-not-to-use rule or routing to the obvious alternative (get_pricing) is given, leaving the agent to infer which tool wins for pricing questions.

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