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

Beyond the annotations (readOnly, non-destructive, non-idempotent), the description discloses substantial behavior: the pricing model and payment rail ($0.01, x402, USDC on Base), the exact time window (91 days ending at the latest reported quarter, never an unreported one), the comparison basis (same weekdays a year earlier), and the granularity/coverage dimensions. This is rich context the annotations cannot convey.

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?

It is a single front-loaded sentence that leads with the metric and price, and every clause carries information. It is dense and parenthetical-heavy, making it slightly hard to parse, but there is essentially no filler.

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 carry the burden of explaining returns, and it partially does so by naming the vs_market_* fields and the company-vs-market comparison. Combined with annotations covering the safety profile, an agent has enough to call and interpret the tool, though return shape details remain partial.

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% and the single 'company' parameter already documents accepted formats (ticker, ISIN). The description adds nothing about the parameter itself, so the baseline of 3 applies when the schema fully carries parameter meaning.

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 names a specific metric (year-on-year growth in point-of-sale sales and units), its scope, and its unit of analysis (per panel store, company and market). This clearly differentiates it from siblings like quote_sales and find_companies, though it never names them. The core purpose is unmistakable.

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 explicit statement of when to choose this tool over siblings such as quote_sales or get_sample. The parenthetical 'vs_market_*, read it first' gives a within-response ordering hint, but that is about reading output, not about tool selection. Usage is implied rather than guided.

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