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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the aggregation behavior and lists the categories, but it does not mention whether the call is read-only, if it requires authentication, how the index is computed (e.g., current vs. cached), or what the response structure contains beyond the category. The description implicitly suggests a read operation via 'get,' but lacks explicit behavioral context.

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, tightly written sentence that front-loads the core purpose ('Get the composite air-quality index') and immediately specifies the aggregation and category levels. There is no extraneous information, making it efficient and scannable.

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 one parameter and no output schema, the description explains what the tool produces (a category) but stops short of describing the exact response format—whether it returns just the category label, a numeric value, or both. It also omits any caveats like error conditions or station validity. Given the low complexity, this is a minor gap, so a 3 is appropriate.

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 description covers the only parameter (station_id) at 100% with 'Numeric station ID.' The tool description adds no additional meaning about the parameter—it does not explain how station_id is used or validated. Per the calibration rule, when schema coverage is high, the baseline is 3, and the description does not elevate it.

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 specifies a precise verb ('get') and resource ('composite air-quality index for a station'), and clearly distinguishes itself from siblings like get_sensor_readings by focusing on the aggregated index rather than raw data. The phrase 'aggregates all pollutants into a single category' makes the tool's 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 gives no explicit guidance on when to use this tool versus alternatives. With sibling tools like get_sensor_readings, it would be helpful to state 'Use this for the overall index; use get_sensor_readings for individual pollutant values.' No such direction is provided, leaving the agent to infer from the 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?

With no annotations, the description carries the full burden. It discloses the time window ('latest ~24 hours') and data format, but does not mention ordering, units, error behavior, or rate limits. This is more than a tautology but still sparse.

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 concise sentences with the key purpose first, then format and time range. No filler or redundant phrasing. Every word adds value.

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 tool with one parameter and no output schema, the description conveys the core behavior (what it returns and the time scope). It does not cover details like sorting order or pagination, but these may be implicit in a simple read operation. Minor gaps remain, but it is 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?

The schema already describes sensor_id well with 100% coverage, including its source ('from get_station_sensors'). The description adds no extra parameter-specific semantics beyond what the schema provides, 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?

The description states a clear verb ('Get'), a specific resource ('recent measurement readings from a sensor'), and the data format ('(measured_at, value) pair'). It distinguishes from siblings like get_air_index (which implies an index, not raw readings) and get_station_sensors (which likely lists sensors, not readings).

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 mentions that sensor_id comes from get_station_sensors, implying a prerequisite call, but does not explicitly state when to use this tool versus alternatives (e.g., get_air_index). No exclusions or conditions 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?

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It clearly implies a read-only operation (listing) and adds useful context about sensor characteristics (each measures a pollutant/indicator). However, it does not disclose any other behaviors such as response format, potential empty results, or pagination. For a simple list tool, this is minimally adequate but leaves room for more specificity.

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 sentence that is front-loaded with the primary action ('List the sensors installed at a station'). It is efficient, avoids redundant phrasing, and includes relevant examples without unnecessary elaboration. Every word contributes to clarity.

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 simplicity of the tool (one parameter, no output schema, no nested objects), the description is sufficient for an agent to call it correctly. It states the purpose and the parameter is documented in the schema. While it does not describe the return structure, that is not critical for a list operation of this type, and the absence of an output schema reduces the expectation for such 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?

The input schema has 100% coverage for the single parameter (station_id), and its description already clarifies that it is a numeric ID from list_stations. The tool description adds no additional meaning beyond what the schema provides. As per guidelines, when schema description coverage is high (>80%), the baseline is 3 even if the description adds no parameter-specific details.

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 uses a specific verb ('List') and clearly specifies the resource ('sensors installed at a station'). It also adds context by naming example pollutants/indicators, which makes the tool's function unmistakable even without reference to sibling tools. This differentiates it from get_sensor_readings and get_air_index, which focus on readings and indices rather than the inventory of sensors.

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 provides no guidance on when to use this tool versus its siblings (list_stations, get_sensor_readings, get_air_index). There is no mention of alternatives or conditions. The only indirect hint is the parameter description in the schema referencing 'list_stations', but that is not part of the tool description itself. An agent must infer the usage context from the name and description alone, which is not 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds genuinely useful behavior (case-insensitive substring matching for both filters, and the overall network scale). However, it does not disclose the return format (fields per station) or any pagination behavior, which matters since there is no output schema.

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 action and resource front-loaded. The filter and scale information is packed efficiently into the second sentence, and 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 3-parameter, all-optional list tool with no output schema, the description covers the essentials: what is listed, filter behavior, scale, and the limit default. The return format is the only notable gap since no output schema exists, but for a straightforward listing operation the description is otherwise sufficiently complete for an agent 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 description coverage is 100% — all three parameters (city, limit, voivodeship) are documented in the schema, so the baseline is 3. The description adds the case-insensitive substring nuance beyond the schema's bare 'Filter by city (substring)', which is a small but real semantic contribution, though not substantial enough to exceed the baseline.

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 (List), a distinct resource (GIOŚ air-quality monitoring stations), and the optional filters. The resource clearly differentiates it from sibling tools (get_station_sensors, get_sensor_readings, get_air_index) which target sensors, readings, and indices rather than the station list itself.

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 useful operational context — the network is ~200 stations, so use filters or `limit` to keep responses small — which signals when to constrain the query. However, it never addresses when to choose this tool versus its siblings (e.g., 'use get_station_sensors for a station's sensors'), offering no exclusions or alternative routing.

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