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

With no annotations, the description carries the full burden and largely delivers: it discloses data provenance (東京都中央卸売市場の日報), update cadence (毎日読み取り), units (1kgあたり・消費税込み), and the comparison baseline (農林水産省の全国470店調査). It does not describe the output shape or explicitly confirm read-only behavior, but the data-source and scope disclosure is unusually substantive.

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 entire definition is one dense sentence with every clause carrying information, and the core purpose is front-loaded. Readability would improve by splitting it into two sentences, but there is no filler or redundancy.

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 gives an agent enough context to know what will be returned and from which sources. Minor gaps remain — the concrete item coverage and how 'today' is determined — but nothing blocks 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 tool has zero parameters, so the baseline is 4. The description compensates for the empty schema by explaining exactly what values come back: per-kg tax-inclusive wholesale prices alongside the national retail average and the resulting multiplier. No parameter-level clarification is needed since there are no 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 names a specific resource and question: how much vegetables and fruits traded today in Tokyo's wholesale market (1kg, tax incl.), read from the Tokyo Metropolitan Central Wholesale Market daily report. It clearly states the tool's function and the retail-comparison angle. However, it does not differentiate itself from the sibling oroshi_item, which presumably covers item-level wholesale lookups.

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?

Usage context is implied rather than stated: an agent can infer this tool answers 'what are today's wholesale prices for veggies/fruit in Tokyo' and shows the wholesale-to-retail multiplier ('市場から店までで何倍になるかが分かる'). But there is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named.

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