vipcars

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

With no annotations provided, the description must carry behavioral disclosure. It does disclose how unknown/unavailable IDs are handled ('listed in not_found'), which is useful. However, it does not state whether the operation is read-only, what happens if fewer than 2 or more than 5 IDs are provided, or any other limitations. The description adds some behavioral context but not enough to fully compensate for the absence of annotations.

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 concise sentences with no filler. The primary purpose is front-loaded in the first sentence, and the behavioral note follows immediately. Every word 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?

Given the tool's simplicity (one parameter, no nested objects, no output schema) and no annotations, the description is mostly complete. It covers purpose, scale, key spec examples, and error handling. It could go further by describing the response shape or behavior for invalid vehicle count, but these are minor gaps for a straightforward comparison tool.

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 describes vehicle_ids only as an array of integers, with 0% description coverage. The description compensates by adding meaningful constraints: it indicates 2-5 vehicles are expected and explains that unknown IDs will appear in 'not_found'. This goes beyond the raw schema, although it does not detail ordering, uniqueness, or exact response structure.

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 a specific verb and resource: 'Compare 2-5 vehicles side by side on key specs.' It clearly conveys what the tool does and the scope, though it does not explicitly name or differentiate from sibling tools like get_vehicle or search_vehicles. The '2-5 vehicles' phrasing implicitly separates it from single-vehicle fetching, but the distinction is not made explicit.

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 the tool: when you need a side-by-side comparison of 2-5 vehicles. However, it does not explicitly state when not to use it or name alternatives such as get_vehicle for a single vehicle or search_vehicles for discovery. Alternatives are only available via the sibling-tools context, not in the description itself.

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 and does so well. It discloses the token's ownership model, that there is nothing to guess or enumerate, that the tool returns only processing status and never customer data, and it enumerates all possible status values with meanings.

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 tightly written, front-loads the core purpose, and every sentence adds value. The security note is brief but important, and the status enum list is clear and complete without unnecessary wording.

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?

Despite having no output schema and no annotations, the description fully equips an agent to call the tool correctly: it explains how to obtain the token, what the operation returns, what it never returns, and the complete set of status values. Nothing essential is missing for this simple single-parameter tool.

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 provides only the parameter name 'session_token' with no description, so the description must compensate. It explains the token's source, its ownership property, and how it is issued, which is highly useful. Slight deduction because the description calls it 'status_token' without explicitly mapping it to the schema's 'session_token' parameter name.

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 verb ('Check'), resource ('processing status of an inquiry'), and provides a strong link to send_inquiry. It is immediately distinguishable from the sibling vehicle-focused tools, and the scope is unambiguous.

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 for when to use the tool: after sending an inquiry with send_inquiry and possessing the status_token from its response. It does not explicitly name alternatives to avoid, but it makes the prerequisite condition so specific that the intended usage is unmistakable.

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 behavioral burden. It discloses that the operation returns public details only, lists the key returned fields, and explicitly states that it raises an error if the vehicle is not available. It does not discuss idempotency or authorization, but for a simple getter this is meaningful and useful disclosure.

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, information-dense sentence followed by a useful error note. It is front-loaded with the core purpose and contains no filler, repetition, or vague wording.

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 simple one-parameter getter with no output schema, the description is largely complete: it defines the target, lists what is returned, and notes the failure mode. It could be slightly stronger by explicitly confirming this is a read-only operation, but 'public details' largely conveys that.

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%, and the description does not mention vehicle_id or explain how the parameter is used, validated, or constrained. The phrase 'of one vehicle' weakly implies that an identifier is needed, but the description adds no real semantic value beyond the property name already present in the schema.

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 a specific verb ('get') and a clear resource ('one vehicle'), and explicitly enumerates the returned content: specs, equipment, condition, description, photo URLs, and listing_url. It is clearly distinguishable from sibling tools like search_vehicles or compare_vehicles because it targets a single vehicle's full 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 clearly implies when to use this tool: when you need full public details for a specific vehicle, as opposed to searching for vehicles or comparing them. It does not explicitly name alternatives or exclusions, but the 'one vehicle' framing provides clear context for selection.

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, the description carries the full disclosure burden and delivers: the return shape {items, total, page, per_page}, listing_url per item, filter values sourced from live inventory in Croatian, and kW units for power. It does not explicitly state read-only behavior or pagination caps, but the search semantics plus the explicit return contract make the operation predictable.

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 tight paragraphs with purpose front-loaded in the first sentence, followed by a compact block of filter/sort/return specifics. Every sentence carries information an agent needs, and the formatting aids scanning. The parenthetical examples add slight density but are justified given 0% schema coverage.

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 18 parameters, zero schema descriptions, no annotations, and no output schema, the description covers the essentials: inventory scope, currency, filter value provenance, units, sort options, and the return contract. Small gaps remain (mileage units, meaning of q, pagination limits), but the likeliest failure modes — guessing English enum values or unknown units — are preempted.

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 compensates for the ambiguous parameters: enum-like filter values are illustrated with concrete Croatian examples ('dizel'/'benzin', 'limuzina'/'suv'), power units are specified as kW, and the sort parameter values are enumerated. Some parameters remain unaddressed (mileage units, q semantics), but the high-risk ambiguities are covered.

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 verb and resource: 'Search the VIP Cars used-car inventory (verified ex-fleet cars, prices in EUR)'. This clearly distinguishes it from siblings like get_vehicle (single vehicle retrieval), compare_vehicles, and the inquiry tools. An agent can immediately recognize this as the browse/search entry point.

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 search semantics imply when to use the tool — it is obviously the find-vehicles operation among siblings — but the description never explicitly names alternatives or states when not to use it. It gives clear operational context (live inventory, filters, sorts) but no exclusion or routing guidance.

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 to lean on, the description carries the full burden and does so thoroughly: it warns about consent before sharing contact details, states there is no payment, reveals the status_token as the only retrieval key, and discloses the per-contact anti-abuse rate limit. This goes well beyond a generic 'send' statement.

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 text is front-loaded with the core action and then packs only high-value warnings and workflow notes. Every sentence earns its place, and the status_token/anti-abuse guidance is clearly delineated.

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 5-parameter tool with no annotations and no output schema, the description supplies the essential behavioral context: the return token, required consent, and rate limit. It is slightly incomplete on parameter-level detail (e.g., message and customer_email semantics), but the description is otherwise sufficient for an agent to call the tool safely.

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 needed to explain parameters, but it only adds meaning for vehicle_id ('optional (omit for a general inquiry)'). customer_email and message are still undocumented even though they are nullable/optional, and no formats or consent specifics are mapped to the contact fields.

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 opens with a specific verb and resource: 'Send a purchase inquiry (lead) to the VIP Cars sales team on the customer's behalf.' It also clarifies the downstream outcome (viewing/test drive) and thereby distinguishes itself from vehicle-lookup and status-checking 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?

It clearly frames when the tool is appropriate (customer wants to inquire about a purchase) and references get_inquiry_status as the later follow-up. It does not explicitly enumerate when not to use it beyond the 'no online payment' note and the anti-abuse limit, so it stops just short of full exclusion guidance.

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