get_linked_laws_from_ordinance

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

With no annotations provided, the description carries the full burden for behavioral disclosure but fails to mention side effects, authentication requirements (apiKey parameter not addressed), error cases, or return format, leaving the agent uninformed about the tool's behavior.

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 extremely concise, consisting of two short phrases that immediately convey the tool's purpose without any extraneous information, making it efficient for parsing.

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?

Despite having 4 parameters and no output schema or annotations, the description is minimal and fails to explain output structure, pagination behavior, or any limitations, leaving significant gaps for an agent to correctly invoke the 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 100%, so the baseline is 3. The description adds no additional parameter information beyond what the schema already provides, offering no further clarification on parameter usage.

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 it queries higher-level laws based on local ordinances ('자치법규 기준 상위법령 조회') and confirms the basis laws, distinguishing it from siblings like get_linked_ordinances (which likely queries linked ordinances from a law) and get_delegated_laws.

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 usage context (when you have an ordinance and need its basis laws) but does not explicitly contrast with alternative tools that perform similar linking operations, leaving potential confusion for an AI agent.

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