Cycle Tracker

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

With no annotations provided, the description fully describes the behavioral traits: returns live availability, includes distance_km when sorted by coordinate, and defaults to sorting by most bikes available. It does not mention destructive actions or other limitations, but the core behavior is well-covered.

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 only two sentences, front-loaded with the main purpose, and every sentence adds value. There is no redundant 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?

Given no output schema, the description provides enough context about the returned data (live availability, distance_km when applicable, sorting by bikes). It could specify the result fields more explicitly, but it is sufficient for an agent to understand the tool's behavior.

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 80% (4 of 5 parameters have descriptions). The description adds context beyond the schema by explaining that without lat/lon, results sort by most bikes available. However, it does not add semantics for the 'limit' parameter, which lacks a schema description. This results in a baseline of 3.

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 finds bike stations with live availability, and distinguishes itself from sibling tools by specifying filtering and sorting options. It uses a specific verb ('Find') and resource ('bike stations in a city'), making its purpose 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 explains when to use the tool (to find stations with filtering by name or sorting by distance) and provides clear behavioral guidance on default sorting without lat/lon. It does not explicitly mention when not to use it or alternatives, but the context is clear given the sibling 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?

No annotations provided, so description bears full burden. It discloses data granularity (10-min snapshots), ordering (newest first), and retention (up to 90 days). However, it omits whether data is read-only (implied), any rate limits, or performance considerations.

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?

Single sentence covers core purpose and key constraints. While efficient, it could be structured more clearly with a separate sentence for parameter explanation. 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?

For a tool with 2 parameters and no output schema, the description adequately explains data shape, granularity, ordering, and history limit. It is sufficient for an agent to understand inputs and expected output, though missing details like error handling or invalid city behavior.

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 has 2 params with 50% description coverage. The description adds meaning by mapping 'hours' maximum (2160) to 'up to 90 days' and implying the time series duration. It does not explain the 'hours' default (24) or that 'city' is required, but overall adds value 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?

Description clearly states the tool provides a time series of bikes available and active stations per city, with 10-minute snapshots, newest first, up to 90 days. This distinguishes it from siblings like find_stations (search) and get_network_status (current snapshot).

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 explicit when-to-use or when-not-to-use guidance is given. The description implies historical trend analysis, but does not contrast with alternatives like get_network_status for current data or get_popular_stations for popularity.

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 full burden. It discloses that data is 'live' and 'refreshes every 10 minutes', adding useful freshness context. It does not cover error handling or authentication, but for a simple read operation, this is sufficient.

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 purpose, and every word adds value. No unnecessary fluff.

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 (1 param, no output schema), the description is fairly complete. It specifies the information returned and refresh rate. Adding a note about the output format would make it perfect, but current level is sufficient.

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 parameter descriptions listing valid city ids. The description does not add additional semantics beyond what the schema provides, so 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 states 'live network totals for a city' and lists specific metrics (bikes available, e-bikes, etc.), distinguishing it from siblings like 'find_stations' or 'get_popular_stations' that focus on station-level or trend data.

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 use for fetching city-level network totals but does not explicitly guide when to choose this over siblings or mention when not to use it. Context is clear but lacks comparison.

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?

Without annotations, the description must disclose all behavioral traits. It only mentions the ranking metric and time window but omits critical details like authentication requirements, rate limits, error behavior, pagination, or update frequency. This is insufficient for a complete behavioral understanding.

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, front-loaded sentence that directly states the tool's purpose without extraneous words. Every part is necessary and efficiently communicated.

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 an output schema and annotations, the description should provide hints about return format, sorting order (descending by average bikes), and error handling. It fails to do so, leaving the tool's complete context incomplete.

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 description does not add any additional meaning beyond the input schema. The schema covers 50% of parameters (city has a list of options, limit lacks description). The description neither explains the limit parameter nor compensates for the missing schema description, leaving parameters underspecified.

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 returns 'busiest stations in a city ranked by average bikes available over the last 24 hours,' specifying both the resource (stations) and the ranking criterion, which distinguishes it from siblings like find_stations or get_availability_trend.

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 is provided on when to use this tool versus its siblings, such as find_stations for general search or get_availability_trend for historical patterns. The description lacks any when-to-use or when-not-to-use information.

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?

Describes a simple read operation with no destructive behavior. Adds context about output fields (ids, map coordinates). No annotations exist, but description is sufficient.

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?

Single sentence with all essential information front-loaded. No superfluous 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?

For a parameterless tool with no output schema, the description fully covers purpose and return content. No gaps.

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?

No parameters, baseline 4. Description adds value by explaining output content beyond the empty 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?

Description uses a specific verb 'list' and resource 'cities', clearly stating the output includes ids and map coordinates. It distinguishes from sibling tools that deal with stations and network status.

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?

Implicitly suggests this tool is a prerequisite by stating ids are used by every other tool. Does not explicitly exclude alternatives, but context is clear.

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