CommercialBuses

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

With no annotations, the description carries the transparency burden. It discloses that the tool returns a single category and related alternatives, which is useful behavioral context beyond the name. Still, it does not explain behavior for unknown slugs, whether alternatives are always present, or what 'in full' concretely includes.

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 a single sentence with no filler. It front-loads the core action ('one bus category in full') before the secondary behavior (related alternatives), and every phrase contributes to understanding the tool.

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?

The tool is simple with one parameter and a fully documented schema, so the description is serviceable for invocation. However, because there is no output schema, the description's vague 'in full' does not fully clarify what fields or structure the agent should expect, and unknown-slug behavior is unaddressed.

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% and the slug parameter description already provides format examples. The tool description adds only that lookup is 'by slug,' which does not materially enhance the parameter semantics beyond the schema, so the baseline score of 3 applies.

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?

Clearly states the tool returns one bus category by slug, which distinguishes it from list_bus_categories ('one' vs. list). The phrase 'in full' hints at comprehensive detail, though it doesn't explicitly name get_buying_context as the sibling it contrasts with, so differentiation is partial but adequate.

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 implies usage when a specific category slug is known, and the promise of 'related categories worth considering instead' suggests a comparison or alternative-seeking use case. However, it does not explicitly state when to prefer list_bus_categories or get_buying_context, leaving usage guidance mostly implicit.

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

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

No annotations are provided, so the description carries the burden. It discloses what the tool does and does not do, which is good behavioral transparency. However, it doesn't describe side effects, return format, or any operational behavior beyond being informational. It's a read-only conceptual tool, but that's not explicitly stated as a behavioral guarantee.

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 a single sentence, but it's packed with useful information: what it explains, what concepts it covers, and a usage directive. It's front-loaded with the core purpose. It could be slightly more concise, but it earns its length by covering the key aspects.

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 zero-parameter, no-output-schema informational tool, the description is quite complete. It tells the agent what the tool covers and when to use it. The only minor gap is not explicitly stating that it returns no data or that it's purely educational, but the description implies this strongly.

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 tool has zero parameters, so the schema is trivially complete. The description doesn't need to explain parameters. Baseline for 0 params is 4, and the description adds context about what the tool covers, which is sufficient.

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 purpose: it explains how sourcing works, what capacity bands and fuel types mean, and what the service does/does not do. It's a conceptual/reference tool rather than a data-fetching tool, which is a specific enough verb+resource. However, it doesn't explicitly distinguish itself from its siblings (get_bus_category, list_bus_categories), though the content described is clearly different.

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 explicitly says 'Read this before telling a buyer what to expect,' which gives a clear when-to-use directive. It doesn't explicitly mention alternatives or when not to use it, but the context is clear: it's a prerequisite reading before using buyer-facing guidance. The sibling tools are category-related, so the usage context is reasonably distinct.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It makes clear the operation is read-only by describing a listing of categories, and it details the exact content returned. However, it doesn't explicitly state that it is a read-only operation, mention any authentication or rate-limit implications, or describe ordering/pagination. For a simple list tool with no parameters, the description is adequate but could have explicitly confirmed non-destructiveness.

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 a single sentence (though technically a fragment) that front-loads the key noun 'commercial bus categories' and then lists the covered attributes. It is reasonably concise, but the lack of a verb makes it slightly awkward and less direct than a phrase like 'Lists all commercial bus categories, each with...'. All included content is relevant, but the structure could be crisper.

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 tool with no parameters, no output schema, and no annotations, the description explains what the agent will receive: each category's definition, typical passenger capacity, operator usage, and CDL endorsement requirement. This is sufficient for the agent to know what to expect from the tool. The only missing detail is the exact format (e.g., list vs. object), but that is minor given the tool's simplicity.

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 input schema has zero parameters and schema coverage is already 100%, so there are no parameter meanings to clarify. The description adds value by explaining what each returned category includes, which is more useful than the empty schema. Since there are no parameters, the description completely compensates for any potential ambiguity.

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 identifies the resource as 'commercial bus categories' and lists the attributes included (what it is, capacity, operator use, CDL endorsement). While there is no explicit verb like 'list' or 'retrieve', the tool name and the phrase 'each with...' make the listing purpose clear. It distinguishes itself from get_bus_category (which likely returns a single category) and get_buying_context (which provides context rather than category details), though it doesn't name those siblings.

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?

No explicit guidance is given about when to use this tool versus the siblings. The description implies it returns all categories, but it doesn't state 'use this to list all categories' or mention that get_bus_category is for a specific category. An agent would have to infer the appropriate use from the tool name and sibling names, so this dimension lacks direct guidance.

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