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

No annotations are provided, so the description must carry behavioral context. It does disclose data sources (agency and ministry) and update frequency (weekly), which is useful. However, it doesn't clarify whether the tool returns a single value or a series, or whether it requires a specific date. The description is sufficient for a simple lookup but lacks depth.

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 a single, compact sentence that packs in the key information: commodities, data sources, geographic scope, and update frequency. No wasted words. It is front-loaded with the main items first.

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 is quite complete. It tells the agent exactly what data is available and the source. Missing details like the exact units (e.g., yen per liter, yen per 5kg) are minor and likely implied. However, it doesn't explain how to access historical data or nuance about the POS data, but those may be out of scope.

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 tool has zero parameters, so the description is the only source of semantics. It fully explains what the tool returns without parameters. The coverage is 100% because there are no parameters to document, but the description adds value by specifying the exact data (gasoline and rice) and sources.

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 states what the tool reports: current prices for gasoline (weekly, from a named agency, across 47 prefectures) and rice 5kg (from a named ministry, POS data, weekly). This distinguishes it from generic price tools, though it doesn't explicitly contrast with siblings like 'super_pos' or 'cost_item'.

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 the use case: get current prices for these specific commodities. It doesn't explicitly state when to use this versus alternatives, but the specificity of the items and data sources suggests it is for current prices rather than historical or index data. No exclusions are given.

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