motocross-tracks

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the non-obvious behavioral detail that results are sorted nearest-first, which annotations and schema cannot convey — genuinely useful context beyond structured fields.

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 short sentences with zero waste; the core behavior is front-loaded before the usage cue. Every clause 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 three-parameter read-only proximity search with full schema coverage and clear annotations, the description is nearly complete. The only missing piece is explicit routing away from search_tracks.

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%, with lat, lng, and radius (including the 100-mile default) all documented in the schema. The description adds no format or unit detail beyond that, 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?

States a specific verb and resource ('Find tracks near a latitude and longitude') and adds the result ordering ('nearest first'), so the agent knows exactly what it retrieves. It does not explicitly distinguish itself from the sibling search_tracks, leaving that gap.

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 one concrete usage cue ('Use for "tracks near me" questions'), which implies the geo-proximity context. However, it gives no exclusion guidance despite search_tracks being a plausible alternative, so the agent must infer which to pick.

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 safety (readOnlyHint=true, destructiveHint=false, openWorldHint=false), yet the description still adds real behavior: results are ordered by date and include ticket links and a race page URL. It doesn't mention result volume or pagination, but that's a minor gap for a bounded per-season list.

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?

One front-loaded sentence delivering scope and payload fields, followed by two short usage examples. No filler 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?

There's no output schema, so the description carries the return-value burden and discharges it by listing exactly which fields come back, in what order, plus how to obtain the input slug. Nothing an agent needs to invoke it correctly is missing.

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 the slug parameter is documented with an example format and its source tool, so the schema does the heavy lifting. The description adds nothing about the parameter beyond that, which is the baseline-3 case.

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 exact resource (every race of one series' season) and even enumerates the returned fields, so an agent can distinguish it from get_track, list_events and list_season_schedules without opening a schema.

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?

Concrete example questions ('when is Supercross in Detroit in 2027', 'the 2027 Pro Motocross schedule') make the intended use case obvious, and the schema points back to list_season_schedules as the slug source. It stops short of stating when-not-to-use or naming list_events as the alternative.

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 read-only and closed-world behavior. The description adds meaningful data-availability context: pricing is only present for roughly half of tracks, and few other sources carry it. It does not cover not-found behavior, but the added context exceeds the annotation baseline.

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 core lookup purpose, followed by a useful emphasis on pricing. No redundant or wasted 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 exists, so the description carries return-value burden and does so by listing address, coordinates, hours, amenities, operating status, upcoming events, and pricing. Combined with annotation coverage, an agent has enough to call 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?

Schema coverage is 100%, so the single slug parameter is already fully documented, including its source from search_tracks. The description repeats 'by slug' but adds no format or validation detail beyond the 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?

States a specific verb and resource: 'Full detail for one track by slug,' and enumerates the fields returned. This clearly distinguishes a single-track lookup from list/search siblings even without naming them.

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 via 'by slug' and the schema points to search_tracks, but it does not explicitly say when to use this tool versus find_tracks_near, search_tracks, or the event/schedule tools. The pricing note is a usage hint but not a selection rule.

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=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds domain scope (which event categories appear) but says nothing about result ordering, whether past events are included, or pagination behavior beyond the schema's limit field. Some added value, but thin against the annotated baseline.

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 short sentences with no filler, and the domain scope is front-loaded before the filtering hint. The first sentence is a noun phrase rather than a verb phrase, which slightly weakens front-loading of the 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?

All parameters are documented in the schema and the annotations carry the read-only profile, so an agent has enough to call the tool. However, with no output schema, the description should indicate what a returned event looks like at a high level (name, date, location) or whether results span future events only; that gap leaves it merely adequate.

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 all five parameters including the series enum example are already documented in structured form. The description echoes state, month, and type but adds no syntax or behavioral detail (e.g., how month interacts with recurring events, or whether series and type are mutually exclusive). 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 names the resource domain (motocross races and events) and enumerates concrete subtypes: Supercross, Pro Motocross nationals, Arenacross, amateur races, practice days. This is more specific than the title and lets an agent know this is an event catalog rather than a track lookup. It does not explicitly contrast with the similarly named sibling list_season_schedules, so it stops short of a 5.

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?

"Filter by state, month or type" implies how to use the tool but never states when to choose it over get_season_schedule or list_season_schedules, nor any when-not conditions. The usage context is inferable from the domain vocabulary 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?

Annotations already declare readOnly, non-destructive and closed-world, so the safety profile is covered; the description adds the useful detail that each entry carries its page plus the series site the dates were verified against and when. That provenance detail is real added context an agent could not get from the empty schema. Not a 5 because nothing is said about ordering, size of the list, or how stale/unverified entries appear.

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 dense sentence with no filler, and the enumeration of schedule families sits up front where it is most useful. The trailing clause ('and the series site its dates were checked against and when') is grammatically tangled and could be split for readability without losing 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?

With no output schema, the description carries the burden of explaining return contents, and it does name the fields: page, verifying site, and check timestamp. Complete enough for a no-argument lister, though a note on ordering or on the relationship to get_season_schedule would close the remaining gap.

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 takes zero parameters, so the baseline is 4; the description correctly makes no parameter claims and signals that no filtering argument exists. The schema coverage figure is moot here.

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?

States the resource precisely — the catalog of season schedules, one per series/season — and grounds it with concrete examples (2027 Supercross, 2027 Pro Motocross, 2026-27 Arenacross). It distinguishes itself only implicitly from the sibling get_season_schedule by describing itself as a collection, so it stops short of the explicit sibling differentiation a 5 requires.

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 catalog-style phrasing implies discovery ('here are the schedules we keep'), which naturally precedes get_season_schedule for a specific one, but that routing is never stated. No explicit when-to-use, and no statement that the tool takes no inputs and therefore cannot be narrowed.

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 this is a safe, closed-world read. The description adds value beyond that by enumerating return fields (name, city, state, slug), which matters because there is no output schema, and by naming the follow-up tool. It omits ranking/matching behavior and whether results are truncated by default.

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, no waste, with the resource scope front-loaded and the follow-up tool named last. Every clause carries 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?

For a zero-required-parameter, read-only search with no output schema, the description covers what it searches and what comes back, which is most of what an agent needs. Missing only relevance/ordering semantics and the default-result behavior that an agent would want before trusting the result set.

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 schema already documents limit, query, state and motorsports formats. The description only restates the filterable dimensions at a high level ('by name, state or discipline') without adding syntax or matching rules, so 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?

States a specific verb (search) and a well-scoped resource (US motocross tracks, off-road parks, training facilities) plus the searchable dimensions. It implicitly separates itself from get_track by forwarding the slug, but says nothing about how it differs from find_tracks_near, the sibling an agent is most likely to confuse it with.

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 search dimensions and the handoff to get_track is explicit, which is genuinely useful routing. However, there is no statement of when to prefer find_tracks_near (proximity) over this tool, and no mention of behavior when no filters are supplied despite all parameters being optional.

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