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

With readOnlyHint, idempotentHint, and destructiveHint=false already provided, there is no contradiction and no need for side-effect warnings. The description adds behavioral value by revealing that include=['reasoning'] changes the response to append a bilingual reasoning narrative, and by characterizing the operation as a fast deterministic lookup.

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 carry purpose, output summary, and the single optional parameter behavior. No filler, redundancy, or tautology.

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 read-only, idempotent two-parameter lookup with an output schema present, the description is complete: it names the required input, the returned fields, and the optional include flag. Nothing needed to call the tool correctly 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 supply parameter meaning; it explains include=['reasoning'] precisely, and identifies cn_code as the known CN code being looked up. The valid digit-length alternatives are left to the schema pattern, which is an acceptable structured constraint.

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 states a specific operation ('lookup') on a concrete resource ('a known CN code') and enumerates what is returned. The word 'known' signals that this is a direct code lookup rather than a classification task, helping distinguish it from klassio_classify_article.

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?

'Fast lookup for a known CN code' clearly tells the agent when to call this tool: when the code is already known. It does not explicitly say 'use klassio_classify_article when the code is unknown,' so it lacks a full when-not/alternative statement, but the context is strongly implied.

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