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

Since no annotations are provided, the description carries the full burden. It discloses the data source (ALIO) and the exact return fields (first-round applicants, competition ratio), which is useful. However, it does not mention whether the operation is read-only, data freshness, pagination, or potential errors, leaving some behavioral 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 two concise sentences, immediately front-loading the primary action and resource. No redundant information exists, and it effectively communicates the core functionality without unnecessary verbosity.

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 lookup tool with no output schema and no annotations, the description covers the essential context: purpose, data source, and return structure. It could mention data recency or fallback behavior, but those are minor omissions for this simplicity level.

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 schema descriptions cover 100% of parameters, so the baseline is 3. The description adds no additional parameter-level detail beyond what the schema already provides (e.g., institution name examples, limit constraints). Thus, it doesn't exceed the schema's own semantic richness.

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 'looks up recruitment competition ratio for Korean public institutions by institution name' and specifies the data source (ALIO) and return values (first-round applicant count and competition ratio). It uses a specific verb and resource, making the purpose unambiguous even without siblings.

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 description provides clear context by scoping to Korean public institutions and ALIO data, making it evident when the tool should be used. It does not explicitly discuss alternatives or exclusions, but with no sibling tools, this is acceptable and does not mislead.

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