Search categories

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

With readOnlyHint=true, the description still adds rich behavioral context: taxonomy hierarchy, search coverage (label/description/search terms), and isNetNeutral semantics. No annotation contradiction; it substantially enhances the safety profile already declared.

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 dense but every sentence serves a purpose. It starts with the main use case, then provides search guidance, examples, hierarchy explanation, and edge cases (isNetNeutral) without redundancy.

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 lookup tool without output schema, the description fully accounts for taxonomy size, search behavior, type filtering, hierarchy, and special flags. It equips the agent to correctly select all relevant leaf IDs for a query.

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 coverage is 100%, but the description adds meaningful examples for `query` ('eating out', 'fuel') and clarifies `type` values (DEBIT=spending, CREDIT=income). It goes beyond the schema by explaining hierarchical filtering implications.

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 opens with 'Find category ids to filter by', immediately stating the tool's verb and resource. It clearly differentiates from sibling analytics tools by focusing on category discovery and filtering.

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?

Explicitly instructs to pass `query` for searching rather than pulling all 180 entries, and clarifies how to filter by DEBIT/CREDIT type. It also advises checking multiple leaf IDs for ambiguous terms like 'food' and explains the meaning of isNetNeutral, giving practical when-to-use guidance.

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