explain_law_structure

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

With no annotations, the description must disclose behavior itself. It specifies the output fields and compact nature, but doesn't mention error handling, permissions, or any edge cases. Since it's a simple read operation, this is adequate but not rich.

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?

Two sentences are used efficiently: the first states the return value and structure, the second provides a comparison and use case. No wasted words.

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 description covers the tool's output structure and use case, and the single parameter is fully described in the schema. It doesn't specify output format or error conditions, but for a summary tool this is reasonably complete.

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 input schema already provides a full description of law_id with pattern and meaning, so baseline is 3. The tool description doesn't add any additional parameter information beyond what the schema provides.

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 returns a compact structural summary of a norm, listing levels with type, id, title, and direct child count. It also distinguishes itself from get_law_structure by being more concise, making the purpose unambiguous.

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?

It explicitly names get_law_structure as a more detailed alternative and suggests this tool is ideal for quickly understanding organization. However, it doesn't explicitly state when NOT to use it, though the contrast implies a trade-off.

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