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

Annotations only declare readOnlyHint and openWorldHint; the description adds real behavioral context beyond them: the exact response sections (summary, distribution, competitors, low_rate, insights), the explicit exclusion of raw listings, and the cost of 50 points per call, which matters for a metered API.

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?

Front-loaded with the analysis scope, then the return shape, then the cost caveat. The English and Korean text largely mirror each other, but the Korean portion carries unique details (median rate, HHI, response keys, no raw list, pricing), so it is not pure duplication.

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?

With no output schema, the description compensates by naming all five response sections and stating what is excluded. The remaining gap is pagination: pageNo/numOfRows are offered but it is unclear whether they paginate aggregates or are ignored, which is genuinely ambiguous for a statistics endpoint.

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 100%, so the schema already carries parameter meaning (bizType enum with default, date formats, pageNo/numOfRows defaults). The description adds nothing about how date ranges or bizType scope the analysis, so baseline 3 applies.

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?

States a specific verb and resource ('Analyze Korean public-sector award results') and enumerates the concrete analyses: success-rate distribution/averages, winner concentration (HHI), and low-rate notices. The note that it returns no raw listings functionally separates it from a raw notice lookup, though the sibling bid_notice is never named.

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 by the 'no raw list provided' caveat, which tells the agent this is for aggregate statistics rather than enumerating postings, but there is no explicit when-to-use/when-not or a named alternative (e.g., bid_notice) for retrieving the underlying records.

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