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

With no annotations, the description carries the full burden. It usefully discloses the kind of content returned (mixture ratio, gear oil, spark plug gap, carburetor settings), which signals a read-only lookup, but it says nothing about permissions, failure behavior when the slug is unknown, or the return structure.

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?

A single compact sentence with the resource stated up front and the returned data parenthetically listed. No wasted words, though the parenthetical could arguably be trimmed.

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 single-parameter read tool with no annotations and no output schema, the description covers what data comes back but omits slug format, error conditions, and any sibling routing. Adequate but with clear gaps for an agent to call it reliably.

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 0% and the single parameter 'slug' is undocumented in the schema, so the description must compensate. It implies the argument identifies a two-stroke scooter model ('某個二行程車款'), giving marginal meaning, but no format or accepted-values detail is provided.

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?

Names a specific verb (取得/get) and resource (保養資料/maintenance data) for a two-stroke model, and enumerates the returned fields (混合比、齒輪油、火星塞間隙、化油器設定). An agent can tell it retrieves maintenance specs, though it does not explicitly contrast itself with the sibling lookup tools like get_model_specs.

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?

There is no guidance on when to choose this over the sibling tools find_part, get_model_specs, or search_models, and no prerequisites or exclusions are stated. The agent must infer that this is the maintenance-specific lookup rather than the general specs lookup.

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