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 clearly states the returned objects (user and wallet) with field details, and specifies the tool's purpose (confirm authenticated account). It does not cover failure modes or auth details, but for a zero-parameter read-only getter, this is sufficient and useful.

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-loads the purpose, then provides return structure and usage in a compact form. Every sentence earns its place with no redundancy.

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 zero-parameter tool with no output schema, the description compensates well by listing returned fields (user, wallet with specific attributes) and offering clear call-order guidance. It fully addresses the agent's likely needs for choosing and invoking 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?

There are zero parameters, so the baseline is 4. The description adds no parameter-level detail (not needed), but it does clarify the context of the call (authenticated account) which indirectly explains why no parameters are required.

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 gets the authenticated ZEVO account and wallet, with a specific verb 'Get' and resource. It distinguishes itself from sibling list tools by focusing on the account owner rather than business data.

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 'Call this first to confirm which account the integration is acting on behalf of,' providing clear when-to-use context. However, it does not explicitly name alternatives or provide when-not-to-use conditions, though the distinction from sibling tools is 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?

With no annotations, the description carries the full transparency burden. It discloses pagination (10 per page, skip), currency units (cents), and that the return shape matches list_receipts. This is meaningful behavioral context beyond the raw schema.

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 compact and front-loaded, with three sentences each adding valuable info: scope, return shape, currency, and pagination. No redundant or filler words.

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 two-parameter tool without an output schema, the description is fully sufficient. It explains the filtering logic, return shape, units, and pagination, leaving no critical gaps for the agent to resolve.

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 complete descriptions for both parameters (bookingId and skip) with 100% coverage. The description adds minimal new semantics about parameters—it only restates the pagination concept that is already in the schema. Thus baseline score 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 the tool's function: 'List receipts for a specific booking'. It specifies the resource (receipts) and the scope (a specific booking), and distinguishes it from sibling tools by mentioning the booking filter and referencing list_receipts.

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 (receipts for a specific booking, available to the API key account) and references the sibling list_receipts for shape, implying when to use it. However, it does not explicitly state when not to use it or compare with get_receipts_by_vehicle, so it lacks exclusionary 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, the description carries the burden of behavioral disclosure. It adds pagination details (10 per page, skip by 10), states amounts are in cents, and notes account-level availability, providing meaningful context. It does not cover error handling or authorization, but for a read-only list tool, the disclosed behaviors are sufficient.

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 short sentences deliver all necessary information: purpose scope, shape reference, currency unit, and pagination. There is no redundancy or filler, and each 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 simple list tool with two params, no output schema, and no annotations, the description covers scope, currency, pagination, and return shape (via pointer to list_receipts). It is slightly dependent on knowing list_receipts' shape, but that sibling is discoverable, making this 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?

Schema coverage is 100% and includes descriptions for both vehicleId and skip. The description reinforces the skip/pagination mechanic (already present in the schema) but adds no new parameter semantics beyond what the schema provides, so a baseline 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 uses a specific verb ('List') and resource ('receipts') with a clear qualifier ('for a specific vehicle'). It also references sibling tool 'list_receipts' for shape, which helps distinguish its scoped purpose 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 clearly states the tool is for listing receipts tied to a specific vehicle, which is a distinct use case from unfiltered list tools. However, it does not explicitly name alternative tools or provide when-not-to-use guidance beyond the scope 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 of behavioral disclosure. It states the operation is a read-only 'List' and explicitly describes pagination behavior ('Returns up to 10 records per page; increase `skip` by 10'). It does not mention error handling, permissions, or what happens with an invalid VIN, which are notable gaps for a tool with no 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 sentences long and front-loaded with the core purpose. Every sentence adds value: the first states what it does, the second gives a use case, and the third explains pagination. There is no redundant or filler content.

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 list-with-pagination tool, the description is quite complete. It covers the input, the return shape via 'Same shape as list_transactions', and pagination behavior. It lacks explicit error handling or output field details, but the reference to `list_transactions` compensates. The absence of an output schema is offset by this reference.

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%, so the baseline is 3. However, the description adds meaningful semantics for the `skip` parameter by explaining pagination ('increase `skip` by 10'), which goes beyond the schema's basic description. It also clarifies that the VIN must be authorized, adding context to that parameter.

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: 'List wallet transactions for one specific authorized vehicle by VIN.' It uses the specific verb 'list' and identifies the resource and filter. It also distinguishes from siblings by noting it targets a single vehicle, unlike `list_transactions` which presumably covers all transactions.

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 use context: 'Useful for reconciling the financial activity of a single Tesla...' It also gives pagination instructions. However, it does not explicitly name alternatives or state when not to use it, though the mention of 'Same shape as list_transactions' implies a comparison.

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 full responsibility for behavioral disclosure. It clearly communicates the filtering behavior, pagination mechanics (10 records per page, skip increments), and response shape (same as list_bookings). This is comprehensive and exceeds typical descriptions.

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 concise and well-structured: it leads with the core purpose, then provides a use case, then adds response and pagination details. Every sentence earns its place with no redundant information or filler.

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 simple interface (one optional parameter, no output schema), the description is remarkably complete. It explains the status filter, response shape, pagination behavior, and use case. The only minor omission is an explicit statement that it is read-only, but the verb 'list' inherently implies that, so the description 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 schema already fully describes the 'skip' parameter, so the baseline is 3. The description adds extra value by explaining exactly how to use 'skip' for pagination ('increase skip by 10 to fetch the next page'), which goes beyond the schema's generic description and is practically useful.

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 function: 'List only ACTIVE bookings for the API key account' with explicit statuses (pre_trip, in_progress, in_termination). It distinguishes itself from the sibling tool list_bookings by focusing on active rentals, and even provides a concrete question it answers ('which vehicles are out on a trip right now?').

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 a clear use case ('Use this to answer...') and clarifies the scope ('only ACTIVE bookings'), which implies when to use it over list_bookings. However, it does not explicitly name list_bookings as an alternative or state when NOT to use this tool, so it falls just short of a 5.

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 burden. It discloses pagination behavior ('Returns up to 10 records per page; increase skip by 10'), the entity's field categories, and the list of statuses. It doesn't cover auth or error behavior, but for a read-only listing tool this is reasonably transparent.

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?

Every sentence earns its place: purpose, entity explanation, use-case guidance, status enum, and pagination. It is front-loaded with the primary action and stays concise given the domain richness.

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 description is complete for a one-parameter, no-output-schema tool: it explains what a booking is, key fields, statuses, and pagination. It doesn't describe return format, but that's not required when no output schema exists, and the content is sufficient for an agent to invoke it correctly.

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 describes the skip parameter (100% coverage), and the description adds meaningful usage detail: 'increase skip by 10 to fetch the next page'. This clarifies the exact pagination mechanism beyond the schema's 'Number of records to skip'.

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 'List bookings (rental/trip records) for the API key account' with a specific verb and resource. It goes further to distinguish itself from siblings by explaining what a booking is and positioning it as the 'best object for who had which vehicle, and when?'.

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 clear usage context: 'Best object for who had which vehicle, and when?' and describes the scope as 'for the API key account'. It does not explicitly mention when not to use it or contrast with siblings like list_active_bookings, but the distinction is reasonably implied.

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 burden of behavioral disclosure. It explains pagination ('Returns up to 10 records per page; increase skip by 10 to fetch the next page'), lists the returned fields, and defines the scope. It does not explicitly state read-onlyness, but 'List' clearly implies a read operation. This is reasonable disclosure for a non-destructive list tool.

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 three tight sentences: purpose and definition, returned content, and pagination. No filler or redundancy. Each sentence adds new, useful information.

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 there is no output schema and no annotations, the description sufficiently covers the output fields, pagination, and scope. It does not explain error handling or the exact JSON structure, but for a straightforward list tool with one optional parameter, it is complete enough for an agent to infer invocation and result interpretation.

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 describes skip, but the description adds operational detail: page size is 10, and skip increments by 10 for pagination. This goes beyond the schema's literal wording and provides actionable guidance for fetching all pages.

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 and resource: 'List inspections' and defines what an inspection is ('a vehicle's condition captured at a point in a booking'). This distinguishes it from sibling tools like list_bookings or list_vehicles. The scope ('for the API key account') adds precision.

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 on when to use this tool: when you need inspection records, including their fields and pagination behavior. It does not explicitly mention alternatives or exclusions, but the resource type is distinct, and the description explains its purpose well enough to avoid ambiguity.

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 full burden and does an excellent job: it discloses cent-denominated amounts, negative values for refunds, included fields, line item tags, and pagination behavior (10 per page, skip by 10). This goes far beyond a minimal description.

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 dense paragraph with no wasted words; every sentence adds useful operational detail. It front-loads the core purpose and then supplies necessary specifics.

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 that there is no output schema, the description compensates richly by enumerating the response contents, currency, status, line item tags, and pagination mechanics. The tool is fully understandable for an agent to invoke and interpret results.

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%; the schema already explains skip as a pagination offset. The description adds 'increase skip by 10' and mentions the 10-record page size, but this is largely redundant with the schema, so the added value is marginal.

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 'List', the resource 'receipts', and the scope 'for the API key account', distinguishing it from sibling tools that filter by booking/vehicle. It also defines receipts as itemized charges, leaving no 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?

It establishes the context as account-wide listing but does not explicitly contrast with siblings like get_receipts_by_booking or get_receipts_by_vehicle. The pagination guidance is clear, but no when-not-to-use scenarios are provided.

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 transparency burden. It discloses pagination behavior ('Returns up to 10 records per page; increase `skip` by 10 to fetch the next page') and explains key fields and statuses. It also clarifies the distinction between receipts and transactions. It doesn't explicitly state that it's a read-only operation, but that is implied by 'list' and the absence of modification language. Overall, it offers substantial behavioral context beyond the schema.

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 reasonably concise given its informational load. It leads with the primary purpose, then provides field context, a note on receipts vs transactions, and pagination details. No sentences are wasted, though the field list is somewhat long and could be trimmed if an output schema existed.

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?

There is no output schema, so the description compensates by listing the key return fields (amount, description, kind, status, etc.) and explaining pagination. For a simple list endpoint with a single optional parameter, this is complete enough for an agent to select and invoke the tool correctly without further documentation.

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 only parameter `skip` is already well-documented in the schema (description covers 100%). The description adds a concrete usage hint: 'increase `skip` by 10 to fetch the next page.' This reinforces the pagination mechanism and gives practical guidance beyond the raw 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 starts with a specific verb+resource: 'List wallet ledger transactions for the API key account.' It clearly distinguishes from siblings, especially list_receipts, by contrasting 'receipts record what was CHARGED; transactions record money MOVING in a wallet.' This makes the tool's unique purpose unmistakable.

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 explicitly states when to use this tool: 'The best endpoint for account statements, wallet history, and payout reconciliation.' It also provides a clear exclusion criterion by contrasting transactions with receipts, telling users to use receipts when they need charging records. This is strong when-to-use 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, the description carries the burden. It discloses pagination behavior (max 10 per page, skip increment), the type of data returned, and account scoping. It does not detail ordering or potential empty results, but the read-only 'list' nature is evident.

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, each adding distinct value: purpose, data contents, and pagination. No fluff, front-loaded with the 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?

The tool is simple (one optional parameter, no output schema). The description sufficiently covers what the tool does, what data it returns, and how to paginate. Missing minor details like field types or response array structure, but not critical for a list endpoint.

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% for the single 'skip' parameter, and the description adds a pragmatic explanation of how to use 'skip' for pagination, complementing the schema's own 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?

The description clearly states the tool lists vehicles available to the API key account, with a specific verb and resource. It distinguishes from sibling tools focused on bookings, receipts, and transactions by explicitly centering on vehicle data.

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 explains when to use this tool: to obtain vehicle IDs/VINs for linking to bookings and transactions. It also provides pagination guidance. It does not explicitly contrast with alternatives, but the intended usage is clear.

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