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

With no annotations supplied, the description carries the full behavioral burden and does well: it discloses cost ($0.05 USDC per call via x402), the payment channel (_meta["x402/payment"]), a free sample mode capped at 3 rows, and a privacy posture ('Facts only; no personal data'). It omits return shape and pagination/limit behavior beyond the sample flag, which is why it is not a 5.

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?

Dense and front-loaded: the framing question is followed immediately by the dataset enumeration, then routes, then pricing. Sentence-fragment style ('Facts only; no personal data.') is efficient rather than sloppy, though the route list and parameter list are compressed enough to read twice.

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?

There is no output schema, so the description must convey what comes back, and it does by enumerating each dataset's contents and time coverage (2025, 2020, FY2019-2024). Payment and sample mechanics are covered; only limit/pagination behavior for full paid calls is left unstated.

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?

Schema coverage is 100%, so the baseline would be 3, but the description adds genuine meaning by mapping each route value to the dataset it returns and to its expected query keys (q, kind, pref, year). That resolves ambiguity the schema leaves open by listing routes without explaining them.

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 (Japanese household official statistics) and enumerates exactly what it contains: 620 spending items with COICOP codes, 80 leisure/sports activities, 301 input-output sectors, household/firm counts by area, and municipal money flows. It stops short of differentiating from siblings such as japan, jp-furusato, or local-markets, so the agent must infer positioning itself.

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 is implied through the dataset-to-route mapping ('/io (q); /actors (kind, q); /spending (q); /activities (q); /local-flows (pref, year)'), which lets an agent pick the right route for a given question. However there is no explicit statement of when to use this tool instead of the many adjacent Japanese-data siblings, and no preconditions or exclusions are given.

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