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

No annotations are provided, so the description bears the full burden. It discloses that the tool creates a rental, the state determines billing start (ACTIVE begins billing immediately), and returns the rental with id and state. It does not mention authentication or rate limits, but the core behavior is clearly communicated.

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: 4 sentences covering the main action, parameter constraints, optional fields, and return value. It is front-loaded with the core purpose, and every sentence adds value without 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?

Given the tool has 6 parameters, no annotations, and an output schema, the description covers the essential behavioral context: creation, state-based billing, and return fields (id, state). It lacks error handling or prerequisites beyond signed-in user, but the output schema reduces the need to detail return structure. Overall it is fairly complete for a creation 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 input schema has 0% description coverage, so the description must compensate. It thoroughly explains all parameters: the mutual exclusivity of vehicle_id and vehicle_code, the meaning of start_rental_state, examples for additions (e.g., insurance, helmet), and the combination of user_group_code and rental_type='BUSINESS' for business billing. This adds significant meaning beyond the bare 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 'Create a rental for the signed-in user', which is a specific verb and resource. It distinguishes from siblings like get_active_rental (read-only) and get_vehicles (listing) by clearly stating it creates a rental, optionally as a reservation or active rental.

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 parameter guidelines: 'Provide exactly one of vehicle_id or vehicle_code' and explains the start_rental_state options. It does not explicitly state when not to use the tool or compare with siblings, but the sibling names provide context. The guidance is sufficient for a typical use case.

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 fully discloses behavior: it returns rentals in specific states and indicates the expected count. It does not mention side effects or permissions, but for a read-only retrieval, this is 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?

The description is concise with two sentences: the first states the main purpose, the second adds important details about states and usage. No unnecessary 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?

Given the output schema exists, the description does not need to detail return values. It covers what the tool retrieves, the states, typical count, and how to use the result with sibling tools. This is complete for the tool's complexity.

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 no parameters, so the baseline is 4. The description does not need to add parameter details, and it correctly focuses on the tool's output.

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 resource ('rentals'), action ('retrieve'), and scope ('signed-in user's currently ongoing'). It distinguishes from siblings by specifying the states ('ACTIVE' or 'RESERVATION') and the usual count of 0 or 1.

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 it (to check current rentals) and provides guidance on next steps ('use a returned rental's id with rental_command'). It does not explicitly state when not to use it, but the context of sibling tools makes the usage clear.

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. It discloses the effect of supplying location (distance annotation, sorting) and the default radius constant, and describes filter behavior. It does not mention authentication or rate limits, but for a read-only list tool this is acceptable.

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 well-structured in two paragraphs, front-loading the core purpose. Every sentence adds value, with no redundancy. At around 150 words, it is concise and easy to parse.

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 has 8 optional parameters, an output schema (so return values need not be detailed), and no required fields, the description fully covers behavior and all filters. It provides sufficient context for an agent to select and invoke the tool 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?

Despite 0% schema description coverage, the description thoroughly explains each parameter's purpose: location scoping with latitude/longitude, default radius via constant, branch_id, category_ids, exclude_stationed_vehicles meaning free-floating only, and min/max state_of_charge as battery percentage 0-100. This adds significant value beyond the schema titles.

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 clear verb+resource statement 'List available vehicles for the signed-in user.' It further explains location-based and non-location behavior, and lists all filters, making its purpose highly specific and distinct from sibling tools like create_rental.

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 states when to include latitude/longitude for spatial filtering and default radius behavior, and explains each filter's effect. However, it does not explicitly state when not to use this tool or directly contrast with siblings, leaving a minor gap.

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. It discloses that END may be blocked by checks and that optional fields are forwarded when relevant. However, it does not describe authentication needs, required roles, success/error response structure, or other behavioral traits like idempotency.

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 well-structured: a summary sentence, a clear list of operation types, a note on optional fields, and a caution about end-checks. Every sentence adds value, though it could be slightly more concise without losing clarity.

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 an output schema exists, the description does not need to detail return values. It covers the core behavior, input parameters, and a notable constraint (end-checks). Some gaps exist (e.g., error handling, idempotency), but for a mutation tool with 6 parameters, it is fairly 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?

With 0% schema description coverage, the description compensates by explaining each parameter: rental_id (required integer), operation_type (case-sensitive list), and optional fields (file_id, parking_report, vehicle_code, reason) with context on when they are relevant (primarily for END). This adds significant meaning beyond the raw JSON 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 clearly states it executes an operation on a rental and returns the updated rental. It lists all specific operation types (START, PARK, etc.) and distinguishes itself from sibling tools like create_rental and get_active_rental, which handle different lifecycle stages.

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 explicit operation types and when to use each, along with context for optional fields (mainly for END). It also warns that END may be blocked by end-checks and that the tool does not pre-run the check/end endpoint. However, it does not explicitly state when NOT to use this tool versus alternatives, though the purpose inherently limits its use.

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