FINN Auto - Car Subscription

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

Annotations already cover key behavioral traits (read-only, non-destructive, idempotent, closed-world). The description adds valuable context about what data is returned (brands with nested models, various filter categories) and the tool's role in validation workflows, which goes beyond the annotations. No contradiction with 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 efficiently structured in two sentences: the first states the purpose and output, the second provides usage examples. Every sentence adds value without redundancy, and it's front-loaded with the core functionality.

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 (0 parameters, rich annotations), the description is nearly complete. It explains the output content and usage scenarios effectively. The only minor gap is the lack of an output schema, but the description compensates by detailing the return structure. For a read-only metadata tool, this is sufficient.

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 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters but adds semantic context about the output's structure (e.g., 'brands with nested models'), which is helpful since there's no output schema. It compensates well for the lack of output documentation.

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 with specific verbs ('Discover', 'Returns') and resources ('all brands, car types, fuel types, colors, subscription terms, gearshifts, and price/power/range bounds'). It distinguishes from sibling tools by focusing on metadata retrieval rather than pricing, details, or search operations.

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 provides when to use this tool ('to answer questions like 'What brands does FINN offer?' or to validate filter values before searching') and implies alternatives by contrasting with sibling tools (e.g., use search_vehicles for actual searches). It gives clear context for usage scenarios.

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?

Annotations already indicate read-only, non-destructive, and idempotent behavior, which the description does not contradict. The description adds valuable context by specifying the return values (base price, km add-on, total, checkout link) and the exact nature of the calculation, enhancing transparency beyond the annotations' safety hints.

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 front-loaded with the core purpose in the first clause and efficiently details the return values in the second. Every sentence earns its place by providing essential information without redundancy, making it highly 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 tool's moderate complexity, rich annotations (covering safety and idempotency), and no output schema, the description is mostly complete. It clearly states the purpose, inputs, and return values. However, it could improve by mentioning any prerequisites (e.g., vehicle availability) or error cases, slightly limiting completeness.

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?

With 100% schema description coverage, the input schema fully documents the parameters (vehicle_id, term_months, km_package) and their constraints. The description adds no additional parameter semantics beyond what the schema provides, such as explaining how these inputs affect the calculation, so it meets the baseline for high schema coverage.

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 specific action ('Calculate exact monthly subscription price') and the target resource ('for a specific vehicle, term, and mileage combination'), distinguishing it from sibling tools like get_vehicle_details (which retrieves vehicle information) or search_vehicles (which finds vehicles). It precisely defines the tool's function without ambiguity.

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 pricing calculation is needed for a vehicle subscription, but it does not explicitly state when to use this tool versus alternatives like get_vehicle_details (which might include pricing) or provide exclusions. The context is clear but lacks explicit guidance on tool selection among siblings.

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?

Annotations cover read-only, non-destructive, idempotent, and closed-world behavior. The description adds valuable context beyond annotations: it specifies that vehicle_id is an 'internal API identifier' and provides UI guidance ('Always show detail_url and checkout_url as clickable links'), which are behavioral traits not captured in annotations. No contradiction with 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?

Three sentences with zero waste: first states purpose and scope, second provides usage instructions, third adds critical behavioral notes. Each sentence earns its place, and information is front-loaded with the core functionality.

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 comprehensive annotations (readOnlyHint, idempotentHint, etc.), the description provides excellent context about what data is returned and how to handle it. The main gap is lack of output schema, but the description compensates well by listing return elements (specifications, equipment, images, pricing, links). Could be slightly more complete with pagination or error handling details.

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%, providing full parameter documentation. The description adds minimal semantic context by clarifying that vehicle_id is an 'internal API identifier' and should come from search_vehicles, but doesn't significantly enhance understanding beyond what the schema already provides. Baseline 3 is appropriate given high schema coverage.

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 verb 'Get' and specifies the exact resources: 'full specifications, equipment, all images, pricing per term, and checkout links for a specific vehicle.' It distinguishes from siblings by explicitly mentioning using vehicle_id from search_vehicles results, differentiating it from get_available_filters and get_subscription_pricing.

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?

Explicitly states when to use: 'for a specific vehicle' and 'Use a vehicle_id from search_vehicles results.' It also provides a clear exclusion: 'never display [vehicle_id] to users,' and implicitly suggests search_vehicles as the prerequisite alternative for obtaining vehicle IDs.

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?

Annotations already indicate this is a safe, read-only, idempotent operation (readOnlyHint: true, destructiveHint: false, idempotentHint: true). The description adds valuable behavioral context beyond annotations: it specifies the return format (prices, images, links), language constraints (German names), and display instructions (show detail_url as clickable, hide vehicle_id). It doesn't mention rate limits or auth needs, but provides useful operational guidance.

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 efficiently structured in three sentences: purpose, language/format rules, and display instructions. Each sentence adds critical information with zero waste, making it easy to parse and front-loaded with essential 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?

Given the complexity (19 parameters, no output schema), the description is reasonably complete. It explains the tool's purpose, key behavioral traits, and output handling. With annotations covering safety and idempotency, and schema covering all parameters, the main gap is lack of output schema details (e.g., response structure), but the description partially compensates by mentioning return fields.

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 schema fully documents all 19 parameters. The description adds minimal parameter semantics beyond the schema—it only reinforces that filter values use German names, which is already covered in schema descriptions for fuels and colors. This meets the baseline for high schema coverage.

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 specific action ('Search available cars on FINN with filters') and resource ('vehicles'), distinguishing it from siblings like get_vehicle_details (which retrieves details for a specific vehicle) and get_available_filters (which lists filter options). It's precise about what the tool does.

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 context for usage by specifying the domain (FINN cars) and language requirements (German names), and it mentions vehicle_id is for get_vehicle_details, implying when to use that sibling tool. However, it doesn't explicitly state when not to use this tool or compare it to all alternatives like get_subscription_pricing.

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