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

Annotations already declare readOnlyHint, idempotentHint, etc., so the safety profile is clear. The description adds valuable context beyond annotations: it explains that verification is human-driven (yes = verified policy, no = human looked and found none, unknown = not verified), and that eligibility depends on returned terms. It doesn't mention rate limits or latency, but for a lookup tool this is sufficient.

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 two sentences, front‑loaded with the core purpose, then details the answer semantics and the dependency on terms. Every sentence earns its place; no waste.

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 no output schema, the description compensates by explaining the return shape (includes verified terms, exclusions, how to claim, quoted sentence, policy page). It clearly defines the three answer states and the conditional nature of qualification. Some gaps remain (e.g., response format specifics), but it is largely complete for an agent to invoke correctly.

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 includes some parameter meaning: 'competitor_price' is echoed back with terms, and 'product' is what the shopper wants to buy. This adds marginal value over the already‑described schema, justifying a 4.

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?

States a specific verb+resource: returns whether a retailer publishes a price-matching policy. It clearly distinguishes from siblings like 'retailers_that_price_match' (list vs. single lookup) and 'price_policy' (broader terms). The description leaves no ambiguity about what the tool does.

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 explains the three possible answer values and notes that qualifying depends on returned terms, which implicitly guides usage. However, it does not explicitly state when to use this tool versus siblings like 'price_policy' or 'retailers_that_price_match'.

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