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

With no annotations, the description carries the burden of behavioral disclosure. It explains that the result is a 'dated record of verified past increases' with source and retrieved date, and explicitly denies being a forecast. This provides useful context about the nature and provenance of the data, though it doesn't detail the exact return format.

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, and every clause adds value. The second sentence explicitly clarifies a critical non-behavior (not a forecast), which efficiently prevents misuse without extra fluff.

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?

For a single-parameter tool with no output schema, the description covers the essential expectations: what the data is (verified past increases), its structure (source + retrieved date), and what it is not (forecast). It could briefly mention the return format (e.g., list) but the wording 'dated record' implies this sufficiently.

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?

The input schema already has 100% coverage with an enum for brand and a clear description. The tool description merely restates the brand names, adding no new meaning beyond what the schema provides. Baseline 3 is appropriate since the schema does the heavy lifting.

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 clearly identifies the tool as a 'retail price-increase ledger' for Hermès or Chanel, with 'a dated record of verified past increases'. It uses specific verbs and resources, and the second sentence explicitly distinguishes it from a forecast, which helps differentiate it from siblings like get_price_history.

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?

It states the tool is for past increases and 'never a forecast', implying this is not for predicting future hikes. It gives the context of the two brands but does not explicitly name alternative tools, leaving the agent to infer that other sibling tools might cover different data types.

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