legal_research

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

Annotations already indicate readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description complements this by explaining that the tool is for complex, multi-API queries and should be fall back for vague natural language queries. No contradiction found.

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 a single dense block of Korean text approximately 400 characters. It front-loads the core concept and lists tasks, but the tasks are embedded in inline text with shorthand and examples that may be hard to parse. The structure is compact but sacrifices readability.

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 12 parameters, no output schema, and no nested objects, the description does a good job of explaining task-switching behavior, parameter dependencies, and fallback rules. It covers the main usage patterns but could be more explicit about the tool's expected output format or response structure.

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 value beyond the schema by explaining the purpose of each task and how task-specific parameters relate (e.g., text required for document_review, domain for dispute_prep). It also clarifies default behavior (e.g., query required for all tasks except document_review).

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 is a Korean law multi-level research integration tool that uses multiple APIs in parallel. It lists 9 specific tasks (e.g., full_research, law_system, action_basis) with examples, effectively distinguishing from sibling tools like search_law and get_law_text which are for simple lookups.

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 explicitly says to use search_law/get_law_text for simple queries that can be answered in a single call. It also defines which scenario values are compatible with which tasks, providing clear context for when to use this complex tool versus alternatives.

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