search_departments

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does convey that the tool performs a keyword-based search and returns department codes, and the examples indicate partial text and numeric codes are accepted. However, it does not explain matching semantics such as case sensitivity, substring vs exact match, result limits, or empty-result behavior, so the behavioral picture is incomplete.

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 one concise sentence that leads with the core purpose and immediately supplies illustrative examples. No words are wasted, and the structure makes the tool's function easy to parse quickly.

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?

The tool is simple with one required parameter and an output schema available, so the description does not need to detail return values. The description covers the core purpose and parameter usage sufficiently. It lacks only explicit guidance on when to prefer alternatives, which is a minor gap for a single-purpose search tool.

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 0%, so the description must compensate for the schema's bare 'query' string property. The description does add meaning by explaining that the query is a keyword for METU department codes and supplies examples, but it leaves the exact expected syntax and matching rules unspecified. It is helpful but not fully detailed.

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 a specific verb ('Search'), a resource ('METU department codes'), and a mechanism ('by keyword'). Concrete examples ('Computer', 'Economics', 'Aerospace', '571') clarify that both textual names and numeric codes are valid. It is distinguishable from sibling tools like get_departments_and_semesters because it focuses on searching codes by keyword rather than listing all departments.

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 implies the tool should be used when the agent needs to find a department code from a partial name or code keyword, but it does not explicitly state when not to use it. It also does not mention alternatives such as get_departments_and_semesters for obtaining the full department list. Usage context is present but left to inference.

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