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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive, so the safety bar is lower; the description adds real value by disclosing the shape of the payload — verbatim pricing-note sentences, read dates, source, and separate measured claims with true/false/not_tested states and review evidence. It also clarifies that vendor claims and measured claims are kept distinct, which prevents misinterpretation.

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 core content is front-loaded, but it is delivered as one sprawling sentence with heavy internal jargon ('our own hands-on claims, exit test and facts') that slows parsing. It is not padded with filler, but structure could be tightened.

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 does useful work describing return contents, so that burden is partly met. However, a two-parameter tool with zero documented parameters leaves an agent unable to construct arguments confidently, which is a material completeness gap.

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 0%, and the description never mentions product_id or the optional cost_trap parameter. 'A product's cost traps' hints at filtering, but there is no explanation of what cost_trap accepts (a name? an id?) or what happens when omitted — the description should compensate for the fully undocumented schema and does not.

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?

It names a specific verb+resource (retrieve the evidence behind a product's cost traps and free-plan flag) and enumerates the evidence types returned, so the purpose is inferable. But it's dense domain jargon ('measured', 'exit test', 'not_tested') and never distinguishes itself from nearby siblings like get_task_evidence or build_purchase_dossier.

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?

There is no guidance on when to call this instead of get_task_evidence, build_purchase_dossier, or compare_offer_costs. The description only says what will be returned, not the situation that selects this tool, so the agent must guess among siblings.

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