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 does explain that the search is spatial ('spatial analytics') and requires coordinates and a radius, but it does not disclose any limitations, accuracy considerations, or what the output list might contain beyond the tool name. This is adequate but not rich.

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 concise sentences, front-loaded with the tool's purpose, then covering parameter requirements. Every sentence contributes meaningful information with no filler.

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 spatial lookup with an output schema present, the description provides sufficient context: what it finds, the required inputs, and the optional parameter. It does not need to explain return values because the output schema exists. It lacks alternative tool guidance, but that is covered under usage guidelines.

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 0%, so the description must compensate. It does by explicitly naming all three parameters: latitude, longitude, and optional radius in meters. This adds meaning beyond the schema's bare type definitions, though it does not specify coordinate format or radius bounds.

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's function (find nearby cooling shelters) with specific verb and resource, and lists examples (parks, pools, libraries, fountains). This distinguishes it from siblings like get_weather_and_heat_risk or get_heat_safety_advice, which serve different purposes.

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 clearly indicates when to use the tool: when you need nearby cooling shelters. It also states the required inputs (latitude, longitude) and optional radius. However, it does not explicitly mention when not to use it or alternative tools, so it falls short of a 5.

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 of behavioral disclosure. It explains the core behavior (returning coordinates) and implies a sequencing behavior ('use first'), but lacks details on edge cases like failed lookups, multiple results, or geographic restrictions. This is minimal but not misleading.

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 extremely concise, with two sentences front-loaded with purpose and usage. The Args section is tightly integrated and adds value without redundancy. Every word 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?

Given the tool's single parameter and existing output schema, the description adequately covers what an agent needs: purpose, usage timing, and parameter semantics. It doesn't explain the return format, but the output schema does, so that's not required. Minor gaps around error behavior are acceptable for a simple tool.

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 provides no description for the 'query' parameter (0% coverage), but the description compensates with an explicit explanation and example: 'The name of the city or location (e.g., "Karlsruhe, Germany")'. This adds meaning and usage guidance that the schema alone lacks.

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's function: 'Get the latitude and longitude for a city, address, or location.' This is a specific verb and resource, and it distinctly separates this tool from its location-based siblings like weather, air quality, and cooling spots.

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 instruction 'Always use this tool first if you only have a city name and need coordinates for the other tools' provides clear context for when to invoke this tool. It implies that this is a prerequisite for other tools, though it does not explicitly list when not to use it or name alternative 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 the description must disclose behavioral traits. It mentions 'live' and that it requires latitude/longitude (already in schema), but does not disclose limitations, units, error behavior, or any safety/read-only nature beyond the verb 'Fetch' implying a read operation.

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 action and data details. Every word is purposeful; no 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?

The tool is simple and an output schema exists, but the description lacks any caution or usage exclusions. It states a use case but not coverage area, data source, or any complementary relationships with sibling tools, making it only minimally complete.

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 0%, so the description must compensate, but it only repeats 'Requires latitude and longitude' without adding meaning like units, coordinate order, or bounds. This adds no value beyond the schema's required fields.

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 the verb 'Fetch' and specific resource 'live air quality data (PM2.5, PM10, AQI)' with an intended use case. This distinguishes it from siblings which focus on weather, cooling spots, or heat risk/advice.

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 clear context: used to assess respiratory safety during heat waves. However, it does not explicitly mention alternatives or when not to use, falling just short of a 5.

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 discloses the valid values for heat_risk_level (LOW, MODERATE, HIGH, EXTREME) and its source, which is valuable context. It doesn't describe output format, but the output schema exists to cover that. No contradictions found.

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 concise: two sentences plus a brief Args section. It front-loads the purpose and keeps parameter details in a structured list. Every sentence earns its place with no redundant 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?

For a simple two-parameter tool with an output schema, the description is complete. It states the purpose, defines both parameters with valid values/context, and notes the data dependency. There are no gaps that would prevent an agent from invoking the tool 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?

The schema is sparse (0% coverage), but the description compensates thoroughly. It defines heat_risk_level with explicit allowed values and activity_type with examples ('jogging', 'construction work', 'elderly care', 'general'), giving an agent enough information to choose appropriate inputs.

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 action ('Get'), the resource ('WHO/CDC safety recommendations'), and the condition ('based on the current heat risk level and the user's activity'). It distinguishes the tool from siblings like geocode_location, get_weather_and_heat_risk, and find_cooling_spots by focusing on safety advice rather than location or environmental 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 explicitly mentions that heat_risk_level is 'obtained from get_weather_and_heat_risk', providing clear guidance on when to use this tool (after fetching the heat risk). It doesn't explicitly state when not to use it or name alternatives, but the dependency implies the correct sequencing and purpose.

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 present, so the description carries the full burden. It discloses the core calculation logic (correlating high temps with drought/soil moisture) but inaccurately states a fixed 7-day forecast despite the schema allowing a configurable 'days' parameter, and it does not mention any limitations or prerequisites.

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 with no filler; it front-loads the primary action and adds a practical use case. Both sentences earn their 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?

The description covers what the tool does and when to use it, but it omits the configurability of the forecast length and does not clarify its relationship to the sibling tool get_weather_and_heat_risk. The presence of an output schema partially compensates for not describing the return format, but overall it leaves 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?

The schema has 0% description coverage, and the description does not explain the latitude/longitude/days parameters. It only mentions '7-day', which hints at the days parameter but does not indicate that it is adjustable or clarify the coordinate requirements.

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 fetches a 7-day weather forecast and calculates a Climate Aggravation Risk, with a specific use case ('predict upcoming heatwaves'). It lacks an explicit differentiation from the sibling tool get_weather_and_heat_risk, whose name suggests overlapping functionality.

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 a clear usage context ('Use this to predict upcoming heatwaves and warn the user'), but does not mention alternatives or exclusions, such as when to prefer get_weather_and_heat_risk or other tools. This fits the 'clear context, no exclusions' level.

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. It only states the coordinate requirement (already present in the schema) and does not disclose read-only status, rate limits, error behavior, or other operational details. 'Fetch' implies a read operation but lacks explicit safety disclosure.

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 main verb 'Fetch', and every word contributes to either purpose or prerequisites. No redundant or extraneous information is present.

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 description covers its core purpose and prerequisite. However, it lacks guidance on selecting this tool over siblings such as get_heatwave_forecast, and does not address potential limitations or error scenarios. Since an output schema exists, return details are not needed, but the sibling differentiation gap remains.

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 0%, so the description must compensate. It merely repeats that latitude and longitude are required without explaining units, ranges, or format. The parameter names are self-explanatory, but the description adds minimal 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?

The description clearly states the tool fetches live weather data (temperature, humidity, UV index) and a calculated WHO/CDC heat risk level. The specific verb 'Fetch' and resource combination distinguish it from siblings like get_air_quality and get_heatwave_forecast.

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 the requirement for latitude and longitude but does not explicitly state when to use this tool versus alternatives like get_heatwave_forecast. The word 'live' implies current conditions, but no clear when-to-use or exclusion guidance is provided.

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