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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, closed-world), but the description adds far more: rows come from a FIXED free sample that cannot be accumulated beyond, aggregates describe the full corpus only at ≥25 matches (with a `population` field signalling which), aggregates are rounded to two significant figures, and absence means absence from the sample only. It also states a citation obligation. This is exactly the behavioral context annotations cannot carry.

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?

Front-loaded with purpose, then layered caveats in tight sentences. It is long, but nearly every sentence carries a distinct constraint (sample cap, threshold, rounding, citation), so little is wasted; only marginally over the ideal length.

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 an output schema present, return-shape explanation is unnecessary, and the description focuses on what the schema cannot convey: sampling regime, aggregation thresholds, the `population` discriminator, and citation duties. Nothing an agent needs to call or interpret this tool correctly is missing.

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 all nine parameters and the sort enum are already documented in the schema. The description's mention of keyword, TLD, price range, year range and venue maps onto parameters but adds no format or syntax detail beyond what the schema provides, so baseline 3 applies.

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 (return a citation sample of real recorded domain sales) and enumerates the filter dimensions. It clearly separates itself from siblings like appraise_domain and find_comparable_sales by stating 'Runs no valuation' and 'actual transactions, not modelled figures'.

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?

Gives concrete example questions, an explicit exclusion ('Runs no valuation'), and routes large-scale needs to an alternative: 'Use the paid Sales Research workspace or API for row-level research at scale.' The when-not condition is stated rather than implied.

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