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 usefully scopes the result to 'active' alerts and named disruption/weather categories, implying a read-only fetch, but says nothing about auth requirements, caching, failure modes, or result shape.

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 compact sentence that front-loads the verb and the resource. No wasted language, nothing to trim.

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 endpoint with no output schema, the description covers what the tool returns (active alerts, disruptions, weather closures) and where they come from. Only minor gaps remain around auth and response structure.

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% for the single required parameter (system_id_or_url), so the schema already documents the accepted ID-or-URL forms. The description adds no parameter meaning beyond what the schema supplies, 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?

States a specific verb (fetch) and resource (active system alerts, disruption notices, weather closures) plus the backing file system_alerts.json. The alert resource is clearly distinct from the sibling station/bike/vehicle-type endpoints, though no sibling is named explicitly.

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?

No when-to-use or when-not-to-use guidance, and no mention of alternatives among the other gbfs_* tools. Usage is only inferable from the fact that it fetches alerts.

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 behavioral burden. It discloses that data is real-time and includes battery levels and coordinates, but says nothing about authentication needs, rate limits, pagination behavior, or whether the endpoint returns empty results for systems without free-floating vehicles. For a network API call with zero annotation coverage, this is thin.

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 that front-loads the verb and resource, then adds key value attributes (battery levels, coordinates). 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 5-parameter network API tool with no annotations and no output schema, the description covers purpose and return content but omits behavioral context like error handling, rate limits, or data freshness caveats. It is adequate but leaves gaps for correct invocation in a production agent.

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 fully documents all five parameters (limit, latitude, longitude, radius_meters, system_id_or_url). The description adds no parameter details beyond what the schema provides. Baseline 3 applies when the schema does all the work.

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 (Fetch) and resource (real-time dockless/free-floating bikes and scooters via free_bike_status.json). Clearly distinguishes from siblings like gbfs_get_stations and gbfs_get_vehicle_types by naming the exact data feed.

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?

No guidance on when to use this tool versus alternatives. It doesn't mention that free-floating vehicles are different from docked stations (gbfs_get_stations) or vehicle types (gbfs_get_vehicle_types). An agent must infer the distinction from the resource name alone.

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 behavioral burden. 'Fetch' and 'real-time' imply a safe read, and it names the returned fields, but it says nothing about authentication, rate limits, pagination, or behavior when coordinates are omitted. Useful but incomplete for a tool with zero 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?

Two sentences, zero filler, with the core purpose front-loaded and the optional proximity behavior second. Nothing could be trimmed without losing 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?

With 5 parameters, no output schema, and no annotations, the definition is largely complete for a simple read tool: purpose, payload contents, and the proximity option are covered. It could do slightly more (e.g., what the response looks like or defaults when coordinates are absent), but the schema handles the required details.

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 every parameter (limit, latitude, longitude, radius_meters, system_id_or_url) is already documented. The description's mention of 'sort and filter by geographic proximity' loosely maps to lat/long/radius but adds no format or interaction details beyond the schema. 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 and resource ('Fetch real-time station status') and enumerates the payload contents (available bikes, e-bikes, docks), so the agent knows exactly what comes back. It does not, however, distinguish itself from siblings like gbfs_get_free_bikes or gbfs_get_system, leaving overlap ambiguous.

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?

Only hints at usage via 'Optionally sort and filter by geographic proximity.' There is no statement of when to prefer this over gbfs_get_free_bikes or gbfs_get_system, no prerequisites, and no exclusions. The agent must infer routing from the names alone.

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 behavioral burden. It does disclose a meaningful behavior: this tool resolves feed endpoints from the GBFS discovery document rather than returning raw data. But it says nothing about error handling for unknown system IDs, network calls to the URL, or latency/caching characteristics of an external fetch.

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 sentence, front-loaded with the verb and resource, every clause earning its place. 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?

No output schema exists, so the description usefully enumerates the returned content (system metadata, operator info, resolved feed endpoints), giving the agent a sense of the response. It is a single-parameter read tool, so little else is strictly required, though failure behavior for bad IDs/URLs is unaddressed.

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 the schema already documents the single parameter with concrete examples. The description restates 'system_id or auto-discovery URL' plus the gbfs.json source, adding only marginal framing beyond the schema. Baseline 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?

States a specific verb (Fetch) and a specific resource (system metadata, operator information, resolved feed endpoints from gbfs.json), scoped to a system_id or URL. This clearly separates it from siblings like gbfs_get_stations or gbfs_get_alerts, which fetch different GBFS feeds.

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 call context (given a system_id or auto-discovery URL, retrieve the discovery document). However, it never states when to prefer this over gbfs_list_systems or when the URL form is appropriate versus the catalog ID form. No exclusions or prerequisites are given.

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 carry the full behavioral burden. It mentions the source file but doesn't disclose whether this is a read-only operation, if it requires authentication, if data is cached, or what the response contains. For a data-fetching tool with no annotations, this is a significant 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?

A single, efficient sentence that front-loads the core purpose and includes specific details about the returned data. No wasted 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 lack of annotations and output schema, the description should do more to explain the tool's behavior, such as read-only nature or response format. It provides some useful detail about the data but leaves key behavioral aspects unaddressed.

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 the schema already documents the single parameter. The description doesn't add any additional meaning about the parameter or its expected format beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (Fetch) and resource (vehicle fleet specifications) and names the source file (vehicle_types.json). It clearly distinguishes itself from siblings like get_stations or get_free_bikes. However, it doesn't explicitly contrast its scope with those siblings, which keeps it from 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?

The description implies the tool retrieves static vehicle type data, but it doesn't state when to use this tool versus get_system or get_stations. No explicit usage context or exclusions are provided.

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 behavioral burden. 'Search ... catalog' strongly implies a non-destructive read, and it discloses catalog size (1,000+ systems), which hints at result volume, but it says nothing about pagination, rate limits, or whether results are filtered server-side.

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 sentence that front-loads the verb and resource, then the searchable facets. Nothing is repeated or padded; 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 simple two-parameter search tool with no annotations and no output schema, the definition covers purpose and searchable scope adequately. However, with no output schema present, nothing describes the return shape or result ordering, leaving a modest gap for an agent deciding how to consume results.

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 both parameters are already documented, giving a baseline of 3. The description adds mild value by enumerating the fields query matches against (city, country, operator, system_id), but contributes no format or syntax detail beyond the schema examples.

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?

Specific verb (Search) plus a clearly named resource (MobilityData systems.csv catalog of 1,000+ bikeshare/micromobility systems) and the searchable facets. It contrasts implicitly with single-entity siblings like gbfs_get_system, but never names them, so the differentiation is inferable rather than explicit.

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 word 'Search' and the catalog scope, but there is no explicit when-to-use guidance and no exclusions. Notably, it does not tell the agent when to prefer this over gbfs_get_system for a known system_id, despite mentioning system_id as a search key.

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