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

No annotations are provided, so the description carries the full burden. It usefully discloses the data provenance (kurashigram.com, CC BY 4.0) and the normalization applied, but it does not describe runtime behaviors such as network dependence, empty results, invalid-code handling, or output format. This is adequate but leaves meaningful gaps.

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, dense sentence that front-loads the core purpose, then adds normalization, source, license, and keying information with no wasted words.

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 simple one-parameter lookup, the description is largely complete: it explains what data is returned (return goods), how it is normalized, and where it comes from. It lacks an explicit output schema and error behavior, but the low complexity makes the likely return shape inferable. This is slightly above minimal viability.

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 provides 100% parameter coverage with '5-digit municipality code', so the baseline is 3. The description adds that the data is keyed by this code, but this is only marginal context beyond what the schema already states.

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 the tool lists Furusato-nozei return goods for a Japanese municipality on Rakuten, with a specific normalization (grams per 10,000 yen). It names the data source and license, and the purpose is distinct from the unrelated sibling tools (GNSS, place, RTK bases).

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 intended use is implied: provide a 5-digit municipality code to get normalized return-good data. However, there is no explicit statement about when to use this tool versus alternatives, nor any exclusions or conditions. The siblings are unrelated, but the description leaves selection guidance to inference.

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