categorize_transaction

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

With no annotations available, the description fully carries the burden of behavioral disclosure. It explains that an LLM is used, that the category is validated against a fixed list, that invalid categories surface as errors, and it specifies the return fields (category, confidence, reasoning). This goes beyond basic expectations and provides meaningful transparency.

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 appropriately sized and front-loaded with the purpose. The only minor issue is the use of 'description:' on a separate line, which could be slightly confusing because it mirrors the tool's own description field. Otherwise, it is structured logically and contains no wasted content.

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?

Given the lack of output schema and annotations, the description covers all essential context: input format with example, output structure with allowed categories and confidence range, and error behavior. Nothing critical is missing for the agent to invoke and interpret the result correctly.

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 schema provides no description for the single 'description' parameter, so the tool description compensates by defining it as 'raw text as it might appear on a statement' with a concrete example ('TESCO STORES 3421 LONDON'). This gives the agent clear semantic understanding that the schema lacks.

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 the tool's function: 'Suggest a budget category for a raw transaction description via an LLM classifier.' This uses a specific verb and resource, and it is distinct from sibling tools like add_transaction or get_spending_summary, leaving no ambiguity about its purpose.

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 context strongly implies when to use this tool: whenever a raw transaction description needs a budget category. It includes an example of the expected input and explains the return structure, making the use case clear. However, it does not explicitly mention when not to use it or point to alternatives, so it falls short of a 5.

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