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

The annotations already mark the tool as read-only, idempotent, and non-destructive; the description adds meaningful behavior beyond that: inputs and results are not saved, English status is internal-only, user-facing output must use statusLabel/summary/professionalConsultation, and unverifiable facts must not be guessed. No contradiction with annotations.

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 dense but every sentence carries distinct operational value: purpose, input sourcing, confirmation rules, output language, and non-retention. It is front-loaded with the core purpose and contains no filler.

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 tool with a complex nested schema and no output schema, the description covers the essential invocation details: provenance, output field usage, and privacy behavior. It omits a concrete output example or possible status values, but these are largely inferable from the schema and context.

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 description coverage is only 33%, so the description compensates by explaining when to populate single_large_owner_percent and related fields (only when the shareholder is confirmed to be a large enterprise under the program) and by forbidding guesses for taxable income and officer overlap. It does not detail every nested field, but it covers the most error-prone semantics.

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 verb and resource: it cross-checks the official treatment of 'deemed large enterprises' against EDINET-verified capital relationships, and distinguishes allowed, excluded, and conditional cases. It does not explicitly name sibling tools, so differentiation is implicit rather than explicit.

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?

It clearly states that the tool applies to candidate subsidies and gives strong input-provenance guidance: program_rule must come from the latest official guidelines/FAQ, with source_url and checked_at. It does not list exclusion conditions or alternative tools, but the context is clear enough for correct selection.

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