Rovv - Book Rides in Africa

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 requirements and the return confirmation, but it does not mention side effects such as payment charges, ride scheduling behavior, or cancellation consequences. It is not misleading, but it lacks depth for a mutation operation.

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, front-loaded with the action and including requirements and return value. Every sentence serves a purpose with no redundant 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 tool with 10 parameters, the description covers the core booking action and return value but omits notable optional behaviors like scheduled rides (is_later, trip_start_time) and payment method options. The schema fills these gaps, but the description alone would not fully prepare an agent for all use cases.

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 100% description coverage for parameters, so the baseline is 3. The description adds little beyond the schema: it repeats the vehicle_type source and mentions payment method generically, but does not clarify the meaning of payment_opt values or the scheduling parameters (is_later, trip_start_time).

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 action and resource: 'Book a Rovv ride.' It distinguishes itself from siblings like cancel_ride and get_current_ride by explicitly indicating a booking action. The return value is also stated, further clarifying its purpose.

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 states a clear prerequisite: 'a vehicle_type ID (from get_fare_estimate),' which tells the agent to use this after fare estimation. It does not explicitly contrast with alternatives like cancel_ride, but the requirement provides useful usage context beyond mere action.

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?

There are no annotations, so the description bears the full burden of behavioral disclosure. It only states it cancels an active ride without detailing side effects, requirements (e.g., whether a valid ride must exist), or irreversibility. The optional reason is mentioned but no further context is provided.

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 front-loaded, stating the core action in one sentence. It could add a brief note about request_id behavior, but it is efficiently written and not wasteful.

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 mutation tool with no annotations or output schema, the description is minimally viable. It states the action and optional parameter but lacks context on success/error behavior or edge cases (e.g., no active ride). More detail would improve 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?

Schema coverage is 100%, with both parameters described in the schema. The description adds nothing beyond what the schema already provides (e.g., 'optional reason' is redundant). Baseline 3 applies.

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 action ('Cancel') and the target resource ('an active ride'). It distinguishes itself from sibling tools like book_ride and get_current_ride by describing a distinct cancellation action.

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 an active ride needs cancellation) and provides context. However, it does not explicitly mention when not to use it or alternative tools, but the purpose is clear enough.

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 must disclose behavioral traits, but it only lists output content. It does not mention behavior when no active ride exists, authentication requirements, or that it is a read-only operation beyond the verb 'Get'. This is a significant gap for a tool that may return an error in edge cases.

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?

A single, well-structured sentence that front-loads the main purpose and lists specific return elements. Every word earns its place, with no fluff or 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?

The description covers the happy path (what data is returned) but lacks details on error handling or the no-active-ride scenario. Given no output schema or annotations, the description is expected to provide this context, making it minimally adequate but not fully 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?

The tool has zero parameters, and the schema inherently covers 100% of them. Per the rubric, a zero-parameter tool gets a baseline of 4; the description adds no parameter info but none is needed.

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: 'Get the status of the user's current active ride' with specific detail about included data (driver details, ETA, ride status). This distinctly separates it from sibling tools like get_ride_history (past rides) and book_ride.

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 phrase 'current active ride' implies the appropriate context (when the user has an ongoing ride) and implicitly rules out use for past or future rides. However, it does not explicitly state when to avoid using it or name alternative tools, so it lacks exclusions.

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 explicitly states the tool 'Returns a list of vehicle options with prices, ETAs, and vehicle type IDs,' disclosing the nature of the output and implying a read-only operation. It doesn't mention side effects or limitations, but for a fare estimate tool, this is sufficient context.

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-loaded with the core purpose, and every word adds value. It avoids unnecessary detail and is well-structured for quick parsing.

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, the description adequately explains the return value (list of options with prices, ETAs, vehicle type IDs). It covers the main purpose and even mentions the importance for booking. However, it could be more complete by noting that either addresses or coordinates can be used as input, and it lacks edge-case behavior, but it is still sufficient for a straightforward fare estimator.

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 has 100% coverage with clear descriptions for every parameter (e.g., 'Pickup latitude'), so the baseline is 3. The description does not add additional meaning about parameters beyond what the schema provides, such as the option to use addresses instead of coordinates. Therefore it neither enhances nor degrades the parameter understanding.

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: 'Get available vehicle types and fare estimates for a trip.' It specifies the resource (fare estimates and vehicle types) and the action (get), and the second sentence clarifies the return value. This distinguishes it from sibling tools like book_ride or get_route_info, which have different purposes.

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 context by stating this tool returns 'vehicle type IDs needed for booking,' indicating it is a pre-booking step. However, it doesn't explicitly state when to use it versus alternatives or provide exclusions, but the context is clear enough for an agent to infer appropriate usage.

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 must disclose behavior. It states the output (coordinates and full address) and the source of place_id, but doesn't mention potential error conditions, permissions, or side effects. The read-only nature is implied by 'Get' but not explicitly stated.

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 sentences, zero filler. The main action and usage context are front-loaded, and every word 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 a simple single-parameter tool with no output schema, the description fully covers the return value (coordinates and address) and its purpose. It doesn't detail the exact output structure, but that's not necessary for an agent to 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?

Schema coverage is 100% for place_id, and the description adds meaning by explaining that the place_id comes from search_places and that the resulting lat/lng are used for fare estimates and booking. This reinforces the schema and provides context beyond the raw field 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 gets exact coordinates and full address for a place, with a specific verb ('Get') and resource ('place details' via place_id). It distinguishes from siblings by explicitly linking to search_places and downstream use for fare estimates and booking.

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 when-to-use guidance: 'Call this after search_places' and 'needed for fare estimates and booking.' It doesn't mention alternatives, but the sequential context and connection to sibling tools make 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, the description is the sole source of behavioral information. It discloses that both completed and cancelled rides are returned, which is useful. However, it does not mention read-only nature explicitly, sorting, pagination, or potential errors, leaving some gaps in transparency.

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 short sentences that state the purpose and what is returned. Every word adds value, and there is no redundancy or unnecessary detail.

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 read tool without an output schema, the description provides sufficient context by stating the return includes recent completed and cancelled rides. It could mention ordering or the effect of the limit, but the schema covers the limit, making the description adequately 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?

The input schema fully documents the 'limit' parameter with a default and maximum, so the description need not add more. The description does not reference the parameter, but schema coverage is 100%, meeting the baseline for adequate semantics.

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 user's past ride history, distinguishing it from siblings like get_current_ride. The verb 'Get' and resource 'ride history' are explicit, and the mention of 'past' and 'recent completed and cancelled rides' adds specificity.

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 for retrieving past ride history but does not explicitly compare with alternatives or state when not to use it. The sibling context shows distinction from get_current_ride, but no direct exclusions are provided, making the guidance implicit rather than explicit.

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 correctly indicates a read-only operation via 'Get' and lists the included outputs (distance, duration, polyline), but does not disclose potential constraints, response structure, or any additional behavioral traits. For a simple read tool, this is adequate but not rich.

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, clear sentence with no filler, front-loaded with the action and key outputs. Every word earns its place, 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?

For a straightforward 4-parameter lookup tool, the description captures the essential purpose and lists the returned data (distance, duration, polyline). With no output schema, it could benefit from a bit more detail on response format or units, but it is sufficiently complete for the tool's 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?

The input schema already provides 100% coverage with clear descriptions for all four parameters (pickup/drop lat/lng). The description adds marginal semantic value by framing them as 'two points', but does not introduce new meaning beyond the schema, so the baseline of 3 applies.

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 the specific verb 'Get' and clearly identifies the resource as 'driving route information between two points' with explicit deliverable fields (distance, duration, polyline). This distinguishes it from sibling tools like get_fare_estimate and search_places, which serve different purposes.

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 route information is needed, but provides no explicit guidance on when to choose this tool versus alternatives such as get_fare_estimate or get_place_details. It lacks exclusions or alternative tool references, so the usage context is only inferred.

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 full responsibility. It discloses the data returned (balance, total added, total spent, recent transactions) and 'Get' implies a read-only operation. However, it doesn't explicitly state safety, side effects, or any prerequisites.

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, focused sentence that front-loads the main purpose and lists the key return data. No unnecessary words or repetition.

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 with no parameters and no output schema. The description lists the specific data returned, which is the primary contextual information needed. It could be slightly more detailed (e.g., currency or limits) but is sufficient for typical 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?

The tool has zero parameters, and the schema already fully covers this with an empty properties object. The description doesn't need to add parameter information, and baseline for 0 parameters is 4.

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 a specific verb ('Get') and resource ('Rovv wallet balance'), and lists the exact data returned. It is naturally distinct from sibling tools, which all focus on rides or places.

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?

Usage context is implied: it should be used when the user's wallet information is needed. However, no explicit guidance is given about when not to use it or alternatives, though for such a simple tool it may not be necessary.

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 the return behavior ('Returns a list of matching places with addresses'), which is the key behavioral trait. It also implies a read-only operation, which is appropriate for a search tool. No contradictions or significant gaps are present.

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 sentences, front-loaded with the action and result, and a clear usage context. Every sentence earns its place with zero 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's simplicity (3 params, no output schema, no annotations), the description adequately specifies the return type (list with addresses) and the primary use case. It could mention optional lat/lng biasing, but the schema already covers that, so the description is complete enough.

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?

Input schema covers 100% of parameters with descriptions, so baseline is 3. The tool description adds no extra parameter information beyond what the schema provides, but it does reinforce that 'query' is the main search term. No compensation needed.

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 'Search' and resource 'a location by name', and explicitly says it returns a list of matching places with addresses. While it doesn't explicitly contrast with sibling tools like get_place_details, the purpose is distinct and 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 a specific use case: 'Use this to find the pickup or dropoff location before booking a ride.' This clearly indicates when to use the tool, though it does not explicitly state when not to use it or mention alternatives like get_place_details.

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