motocross-tracks

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only adds 'nearest first' as a behavioral trait; it does not state whether the operation is read-only, whether auth is needed, what happens when no tracks match, or how results are returned. With no output schema, this is a meaningful gap.

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 redundancy. The core action and ordering behavior are front-loaded, and the usage cue follows without padding.

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 and the schema covers all parameters, but there is no output schema or annotations. The description handles purpose and usage well but leaves return format, failure behavior, and edge cases unspecified, so an agent is missing some execution detail.

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 explains lat, lng, and radius. The description adds 'nearest first' and frames the parameters as the center of a proximity search, but does not meaningfully extend parameter semantics 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 ('Find tracks'), the spatial constraint ('near a latitude and longitude'), and the ordering ('nearest first'). This clearly distinguishes it from search_tracks and list_events without needing to open the 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?

Explicitly ties the tool to 'tracks near me' questions, giving a clear trigger context. It doesn't explicitly discuss when to prefer a sibling like search_tracks, but the usage cue is sufficient for the common 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?

The description goes beyond the name by enumerating the returned fields and noting that pricing is conditional ('where it has any'), which is useful behavioral context. However, with no annotations, it does not cover potential error behavior, output shape, or security requirements, leaving some gaps.

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 with no filler: the first states the tool's purpose and full field list, the second adds a valuable, actionable note about pricing. Every word earns its place and the key purpose is front-loaded.

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 adequately compensates for the absent output schema by listing all expected data fields, including the conditional pricing. It could add error behavior or a pointer to search_tracks for obtaining slugs, but the schema already covers slug provenance.

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 schema already describes 'slug' as 'Track slug, from search_tracks'. The description only restates 'by slug' and adds no new parameter details, so it does not meaningfully exceed 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?

The description names a specific verb and resource: get full detail for one track by slug. It lists the exact data fields returned and clearly distinguishes itself from sibling search/list tools by being the single-track detail endpoint.

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 clearly states the use case: retrieve full detail for one track when you have a slug. The pricing note adds a concrete reason to prefer this tool, though it does not explicitly name when to use alternatives like search_tracks or find_tracks_near.

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 carries the full burden. It only names event categories and filters; it does not disclose return format, pagination behavior, sorting, combination rules for filters, or whether any side effects exist. Being a 'list' command implies read-only, but the description itself does not articulate this or other behavioral traits.

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 short sentences with no filler. It front-loads the subject, provides concrete examples of event types, and ends with the filtering options. Every word contributes to understanding the tool's scope.

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 adequate for a simple list tool with four optional parameters and a fully documented schema. It covers the event domain and filter dimensions. It could be slightly more complete by stating that the tool returns a list or how filters combine, but the terms 'list' and 'filter' convey enough for correct invocation.

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 covers all four parameters (type, limit, month, state), so the baseline is 3. The description adds modest semantic value by listing event categories and grouping filter dimensions, but it does not substantially explain parameters beyond the schema's own descriptions.

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 resource as Motocross races and events, enumerating specific event categories and stating the available filters. The name 'list_events' plus the description of event types distinguishes this from sibling tools that are all track-related (find_tracks_near, get_track, search_tracks).

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 you need to see Motocross events and filter them by state, month, or type. However, it does not explicitly contrast it with alternative tools, state when not to use it, or mention any relationships to the sibling track tools.

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 must convey safety and behavior; 'Search' signals a read-only operation and the return fields are listed, but it does not disclose pagination, sorting, match behavior, or any access requirements. Acceptable but minimal.

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, each earning its place: first defines action and scope, second names what is returned and links to get_track. 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?

For a search tool with no output schema or annotations, the description covers purpose, scope, and return fields, but omits guidance about the location-based sibling, whether at least one filter is required, and result ordering/pagination beyond the schema's default.

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?

All 4 parameters are fully described in the schema, so the baseline is 3. The description adds some context by naming the three search criteria, but uses 'discipline' where the schema calls it 'motorsports' and adds no new detail about limit or query 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?

Clearly states a specific action (search) on a defined resource (US motocross tracks, off-road parks, training facilities) with explicit search dimensions (name, state, discipline). It also points to get_track via slug, but does not explicitly contrast with the location-based sibling find_tracks_near, so it's not a full 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?

The description implies the search-to-get_track flow by mentioning the slug, but gives no explicit when-to-use or when-not-to-use guidance, and is silent on the location-based alternative find_tracks_near.

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