FINN Auto - Car Subscription

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds detail on what data is returned (brands, models, fuel types, etc.), providing context beyond annotations. No contradiction.

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 front-loaded with purpose. No filler; every sentence adds value.

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 no parameters and no output schema, the description adequately explains the tool's purpose and return values. It mentions nested models but could note response structure slightly more, though still 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?

No parameters exist in schema, so schema coverage is 100%. The description adds no parameter info but explains the return content, which is appropriate given zero parameters.

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 discovers available fleet options, listing specific categories (brands, models, car types, etc.). It distinguishes from siblings like search_vehicles by focusing on available filter values rather than search.

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?

Explicit usage guidance: 'Use this to answer questions like...' and 'to validate filter values before searching.' This tells the agent when to use it and implies when not (e.g., for actual searching, use search_vehicles).

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. The description adds valuable context beyond annotations: it specifies that three different funnel URLs are returned per model (marketing, subscription, leasing), which helps the agent understand the output structure and use cases. 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 front-loaded with the core purpose, followed by specific details about URL types and usage guidelines. Every sentence adds value without redundancy, making it efficient 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, and 100% schema coverage, the description is largely complete. It explains the three URL types and their use cases, though without an output schema, it could benefit from more detail on the return format. Still, it provides sufficient context for effective use.

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 both parameters. The description adds marginal value by clarifying that omitting 'model' returns all available models, but this is also covered in the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 resource 'canonical FINN URLs for a brand and its models', specifying it's for building internal linking blocks on SEO pages. It distinguishes from siblings by focusing on URL generation rather than filtering, 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?

Explicit guidance is provided: use `plp_leasing_url` when linking from a Leasing advisory, and `plp_subscribe_url` when linking from subscription content. It also clarifies that omitting the model parameter returns all available models for the brand, offering clear alternatives within the tool 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?

Annotations indicate readOnly and idempotent, which are consistent. Description adds details on URL structure and down payment behavior, enhancing transparency beyond 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?

Well-structured with main purpose upfront, followed by URL details and down payment explanation. Some redundancy in URL examples, but overall concise and easy to scan.

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?

Covers inputs, behavior, and return values (base price, km add-on, total, checkout URL). No output schema, but description sufficiently explains output. Missing error handling guidance, but acceptable given 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?

Schema description coverage is 100%. Description adds value by explaining allowed values for km_package and term_months, and explains how down_payment_amount affects pricing and URL.

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?

Clear verb 'calculate' and specific resource 'monthly subscription price' for a vehicle, term, and mileage combination. Distinct from siblings which handle filters, vehicles, and search.

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?

Provides explicit guidance on using the returned checkout URL verbatim and explains when to include down_payment_amount. Does not explicitly state when not to use the tool, but purpose is self-explanatory.

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 declare readOnlyHint, idempotentHint, destructiveHint. Description adds behavioral context: returns specifications, images, pricing, and detail_url; explains relationship with other tools. No contradiction.

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?

Concise and well-structured: one sentence for purpose, followed by key usage instructions and warnings. No unnecessary text.

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?

No output schema, but description fully explains return values (specifications, equipment, images, pricing per term, detail_url) and how to use them with other tools. Complete for this 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?

Schema has 100% coverage. Description adds value by noting that vehicle_id is an internal API identifier never to be displayed to users, going beyond schema description.

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?

Description clearly states 'Get full specifications, equipment, all images, and pricing per term for a specific vehicle,' specifying verb+resource+scope. It distinguishes from siblings by advising to use vehicle_id from search_vehicles.

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?

Explicit usage guidance: use after search_vehicles, always show detail_url as clickable, never display vehicle_id, and use get_subscription_pricing for checkout links. Includes when-not-to (constructing URLs) and refers to sibling tool.

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 declare readOnlyHint, idempotentHint, and destructiveHint. Description adds context about return content and display rules, but does not expand on behavioral traits like rate limiting or pagination beyond what schema covers.

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 concise sentences: purpose, filter note, and important display guidelines. No redundancy, front-loaded with core action.

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 19 optional parameters and no output schema, the description covers return behavior and critical display instructions. It references sibling get_vehicle_details via vehicle_id. Missing default sort order explanation, but this is minor given 100% schema parameter coverage.

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%, providing baseline of 3. Description adds value by emphasizing that filter values (colors, fuels, etc.) must use German names, which is not obvious from schema alone.

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 it searches available cars with filters and returns matches with prices, images, and links. However, it does not explicitly distinguish from sibling tools like get_vehicle_details or get_available_filters beyond mentioning vehicle_id redirection.

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?

Provides crucial guideline that filter values must use German names and display instructions for detail_url and vehicle_id. Lacks guidance on when to use this tool versus siblings, such as using get_available_filters to discover acceptable filter values.

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