Open Paddock

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

Annotations already declare the tool as read-only, idempotent, non-destructive and not open-world, but the description adds substantial context beyond them: result fields, distanceMi only when near is set, Open Paddock's neutral no-booking role, booking via bookingUrl, and required attribution for MotorsportReg rows.

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 and then adds necessary result, booking and attribution guidance. Despite covering complex contractual requirements, every sentence carries operational meaning and there is no 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?

With 11 optional parameters, no output schema and read-only annotations, the description compensates well: it lists the returned fields, explains conditional fields like distanceMi, clarifies the kind values, and specifies required user-facing attribution and booking routing.

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 high at 91%, so the schema already documents most parameters. The description still adds interpretation by explaining when to use near versus from/to, how sort=distance depends on near, and how to present the kind values.

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 states a specific resource and scope: upcoming motorcycle track days in North America, ordered by date or distance. It does not explicitly distinguish this from siblings such as get_event or list_circuits, so it is clear but lacks sibling differentiation.

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 gives useful query guidance, such as using near for 'track day near Sacramento' questions and from/to for a month. However, it does not say when to use this tool versus get_event or other siblings, and gives no exclusions or alternatives.

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 establish that this is a read-only, idempotent, non-destructive operation. The description adds substantial behavioral context beyond annotations: the returned fields, the limit of up to 20 upcoming days, booking redirect behavior, and required attribution for MotorsportReg.com data.

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 what the tool returns, then moves into policy and attribution guidance. It is dense but mostly earns its length, since the booking and attribution details affect how the agent should present the result.

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 no output schema, the description must explain return contents, and it does so clearly: circuit details, organisers, and upcoming days. It also covers the important downstream behavior around booking and attribution, leaving little needed for correct invocation and presentation.

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%, and the id parameter is fully documented with an example and a name-based fallback. The description does not add meaning beyond the schema for the single parameter, so the 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 identifies the resource and scope: one circuit with location, length, turns, organisers, and next upcoming days. This distinguishes it from list_circuits by focusing on a single circuit, though it does not explicitly name sibling alternatives.

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 important post-retrieval guidance about booking through the organiser and checking details there, plus attribution requirements. However, it does not explicitly state when to use this tool versus list_circuits, find_track_days, or get_event, leaving selection guidance mostly implied by the name and schema.

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?

Beyond the read-only and idempotent annotations, the description adds important behavioral context: Open Paddock is a neutral calendar, sells nothing, takes no bookings, and users must be directed to the organiser's site. It also discloses source-specific handling for MotorsportReg rows and required attribution, which an agent could not infer from 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 retrieval purpose and id source, followed by necessary operational and attribution requirements. Every sentence carries useful information, and there is no redundant restatement of the tool name or schema.

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 lookup with rich safety annotations, the description provides enough context to call the tool correctly, including id sourcing, bookingUrl handling, openPaddockUrl linking, and attribution rules. It does not describe error behavior or not-found cases, but it covers the main completeness needs 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?

The input schema has 100% description coverage and already explains that id is an event id or openpaddock.app/events URL. The description adds that the id can come from find_track_days, but it does not add meaningful syntax or format details beyond what the schema provides, so the 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 that this retrieves one listed track day by id, and it names the id sources (find_track_days or an openpaddock.app/events link). It does not explicitly contrast the tool against get_circuit, list_circuits, or list_organisers, but the resource and access pattern are clear.

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 gives clear usage context: call this with an id obtained from find_track_days or an event URL. It also explains the downstream booking flow and attribution requirements, though it does not state explicit exclusions or alternatives beyond the id source.

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=false. The description adds useful behavior beyond that: the result includes city, state, region, and upcoming-day counts, and the near parameter filters and sorts by distance while adding distanceMi. It does not cover auth or rate limits, but that is a minor gap given the annotation coverage.

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, front-loaded with purpose, then parameter behavior, then next-step guidance. No sentence is wasted, and the flow from what it returns to how near changes behavior to how to use the id is logical and efficient.

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 no output schema but annotations covering the safety profile, the description gives enough context to invoke the tool correctly: scope, returned fields, near behavior, and downstream id use. The region parameter's filtering semantics remain unexplained, and pagination behavior is unstated, so it is 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?

Schema description coverage is 67%: near and within_miles have schema descriptions, but region only has an enum. The description meaningfully extends near by explaining that it restricts to within_miles, sorts nearest first, and returns distanceMi, which is not in the schema. It leaves region undocumented, so it does not fully compensate for the coverage gap.

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 states a specific verb and resource ('Motorcycle circuits Open Paddock knows') with geographic scope and the fields returned. It also routes the agent to downstream tools by mentioning the id for find_track_days or get_circuit, which helps position it among siblings, though it never explicitly contrasts itself with list_organisers or get_event.

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 is implied by the tool name and the downstream hint ('Use the id with find_track_days or get_circuit'), but there is no explicit statement of when to call this tool versus alternatives or any exclusions. The agent can infer it is the circuit listing endpoint, but the description stops short of real routing 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?

Annotations already cover read-only/idempotent/closed-world, so the description adds genuinely new behavior: entries come in two states, 'dates listed' or 'link only', and link-only records carry no readable calendar so the agent must redirect the user to the organiser's website. That is real operational context not available elsewhere.

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 that carry real information with little padding, but the phrasing is awkward — the embedded quotation of 'dates listed' is clumsy and the opening sentence lacks a verb, making it read like a data dictionary entry rather than a tool instruction.

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 only two optional enum params and no output schema, the description covers the necessary ground: what the list contains, the two record states, and how to act on them. It stops short only on whether the result is paginated or what fields each entry carries.

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 50%, and the description fills the gap for `region` by clarifying it is the region of the circuits the organiser runs at, not the organiser's own location — a meaningful disambiguation. The `type` values are already enumerated in the schema, so no further credit there.

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 names the resource precisely (track-day organisers, schools, clubs) and describes the two listing modes, which lets an agent separate it from list_circuits and find_track_days. The first sentence is a fragment with no explicit verb, so the 'list' action is only implied by the name.

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 gives filtering guidance ('Filter by the region of the circuits they run at, or by organiser type') and a handling rule for link-only entries, but never states when to choose this over the sibling tools or what prerequisites apply. Usage is inferable rather than explicit.

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