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

No annotations are provided, so the description carries the full burden. It discloses the tool is a read-only operation ('Get'), returns an 'estimated offer range and next steps', and requires certain inputs. However, it does not explain potential side effects, whether actual offers are binding, or the role of zip/mileage. This is adequate but not rich.

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 two sentences, front-loaded with the core purpose, then input requirements, then output. Every sentence adds value, with no unnecessary words or repetition of schema details.

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?

With 5 parameters, no annotations, and no output schema, the description could do more. It explains the VIN/license plate requirement but leaves ambiguity: the schema marks all params as optional, yet the description implies mandatory inputs. It also doesn't describe the role of zip/mileage, though these are in the schema. Overall, reasonably complete but with notable gaps.

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 covers all parameters with descriptions, giving a baseline of 3. The description adds meaning by explaining the relationship between VIN and license plate ('VIN or license plate + state'), clarifying the alternative input methods beyond the schema. This adds value to parameter usage context.

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 identifies the tool's purpose with a specific verb and resource: 'Get an instant cash offer from CarMax for selling your car.' It also distinguishes itself from sibling tools like search_inventory and schedule_test_drive by focusing on the selling/offer scenario, not buying or scheduling.

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 provides clear usage guidance: 'Provide VIN or license plate + state' and states what the tool returns. While it doesn't explicitly compare to alternatives, the purpose is distinct, and the prerequisite information is useful. It does not mention when not to use or list alternatives, but the context is clear enough.

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 for behavioral disclosure. It accurately describes the response contents, making it clear this is a read-only retrieval operation. However, it does not comment on side effects, error behavior, or limitations, and the mention of 'URL slug' is misleading since the schema only accepts stock_number. This partially undermines 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 a single, front-loaded sentence that efficiently communicates the tool's purpose and highlights key data categories. It omits unnecessary filler. The only flaw is the inclusion of the inaccurate 'or URL slug', which could have been omitted for greater precision, but overall it is appropriately concise and well-structured.

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 simplicity of the tool (one parameter, no output schema), the description adequately covers the main use case by specifying the identifier and the expected response contents. It lacks details on error handling or the fact that URL slug is not a supported parameter, but for a straightforward get-by-id tool it is reasonably complete.

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 already provides a thorough description of the stock_number parameter (with example and source), giving a baseline of 3. However, the description introduces an unsupported alternative, 'URL slug', which is not present in the input schema. This creates confusion about accepted inputs and adds misleading semantics, warranting a penalty to 2.

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: 'Get full details for a specific CarMax vehicle' with a specific identifier ('stock number or URL slug') and lists the types of data returned (specs, features, photos, Carfax history, store location). This distinguishes it from sibling tools like search_inventory (searching) and schedule_test_drive (booking).

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: use this when you have a specific vehicle identifier and need detailed information. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'use search_inventory to find the stock number'), nor does it mention any exclusions. The guidance is implied rather than explicitly stated.

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 does disclose the outcome ('confirmation details or next steps') but doesn't mention permissions, confirmation behavior, what happens if the slot is unavailable, or whether this is a firm booking or request.

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 sentences, no fluff, directly states purpose and outcome.

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?

With 7 parameters, no annotations, and no output schema, the description gives only a high-level outcome. It lacks detail on handling conflicts, appointment confirmation mechanics, or what 'next steps' means, making it adequate but not complete.

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 100%, so the baseline is 3. The description adds no parameter semantics beyond 'specific vehicle', leaving the schema to fully document each field.

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?

Specific verb 'schedule' identifies the action, resource 'test drive appointment at CarMax' is clear, and 'for a specific vehicle' scopes it. This distinguishes it from siblings like search_inventory and get_vehicle_details.

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 use when booking a test drive but provides no explicit guidance on when to use this vs. searching inventory or getting vehicle details first, nor any exclusion criteria.

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 full burden of behavioral disclosure. It describes what the tool does (search) and the return payload (list of matching vehicles with stock numbers, prices, mileage, links), which effectively communicates a read-only search operation with no side effects. It does not disclose pagination, rate limits, or prerequisites, but for a search tool this is adequate.

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 concise sentences that front-load the core purpose, then list filters and return content. No redundant words or repetition of schema details. Every sentence earns its place.

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 search tool with 8 optional parameters and no output schema, the description is reasonably complete. It explains the resource, the filters, and the return fields. It doesn't cover edge cases like default behavior or sort order, but it provides enough context for an agent to invoke the tool correctly and understand the response.

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 covers all 8 parameters with descriptions, and the tool description echoes most of them ('make, model, year range, price range, location'). However, the description does not add extra meaning beyond the schema—for instance, it doesn't clarify format nuances or defaults. With 100% schema coverage, the baseline of 3 is appropriate.

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 'Search CarMax inventory for used vehicles' with a specific verb and resource, and lists the available filter dimensions. This distinguishes it from sibling tools like get_vehicle_details, which focuses on details for a specific vehicle, and schedule_test_drive/get_instant_offer, which are unrelated actions.

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 when to use this tool—when searching for used vehicles that match certain criteria—and provides a clear context. It does not explicitly mention when not to use it or name alternatives, but the sibling tools are sufficiently different that an agent can infer the appropriate use case.

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