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

With no annotations, the description carries the full burden, and it does so thoroughly. It discloses that prices are human-read, includes both base and tax-included prices, specifies the exact tax verification formula (1.08, with 1.10 for alcohol and daily necessities), and explicitly states '推定なし' (no estimates). This gives an agent strong expectations about data provenance and quality.

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 three sentences with no filler. The core subject and resource type are front-loaded, followed by concrete chain names and validation details. Every sentence adds meaningful information, and the structure is easy to scan.

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 zero-parameter tool with no output schema, the description does a good job of explaining what the returned list contains and its coverage. It names all included chains, specifies the price types, and defines validation rules. It could be slightly more complete about output formatting or update behavior, but nothing critical is missing for correct invocation.

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 is empty, so there are no parameter semantics to explain; the baseline of 4 applies. The description provides useful context about what data fields are present (chain, prefecture, period, item count, prices), compensating for the absence of a structured schema without needing to explain specific parameters.

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 providing a list ('一覧') of actual supermarket selling prices read from official flyers, including chain, prefecture, publication period, and item count. It names specific chains and validation criteria, making the resource distinct. However, it does not explicitly differentiate itself from sibling tools like chirashi_chain, so it stops short of full clarity.

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 implies when to use the tool—when you need verified price data from these named regional supermarkets—but gives no explicit guidance on when to prefer an alternative. With many sibling tools in the same domain, the lack of any 'use this instead of X' or exclusion criteria is a notable gap.

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