Lookup Classification

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

With no annotations, the description carries the behavioral burden. It explains the two modes of operation (whole table vs. specific code subtree) and clarifies what each system represents. It does not discuss errors or auth, but for a read-only lookup tool the disclosed behavior is sufficient.

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 compact sentences deliver all key information without redundancy. The main action is front-loaded, and the parameter explanations are woven in efficiently. Every clause adds value.

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 tool's low complexity (2 params, no nested objects) and the presence of an output schema, the description covers all essential aspects: what systems are supported, how the optional code changes the result, and what outputs to expect. No critical information is missing.

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 0%, so the description must explain the parameters. It does: 'system' values are named and defined (mcoicop/msic), and 'code' is described as optional, including example types ('division or section letter') and its effect on output. This compensates well for the empty schema descriptions.

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 uses specific verbs ('look up', 'traverse') and names the exact resources ('DOSM classification system' with 'mcoicop' and 'msic'). It clearly differentiates this tool from data-series siblings by focusing on classification metadata and stating what each system means.

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 gives clear context on how to use the tool: pass 'code' for a specific entry and its subtree, or omit it to get the entire table. It doesn't explicitly compare against sibling tools or state when not to use it, but the classification-specific purpose makes the use case evident.

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