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 states the transformation function but lacks critical details: it doesn't specify accuracy levels, rate limits, error handling (e.g., for invalid addresses), data sources, or output format (e.g., coordinate precision). For a geocoding tool with zero annotation coverage, this is a significant gap in transparency.

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—a single sentence in Chinese that directly states the tool's function without any fluff. It's front-loaded with the core purpose and wastes no words. Every part of the sentence earns its place by clearly communicating the transformation.

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 is incomplete for effective tool use. It doesn't cover behavioral aspects like error handling or performance, and while the input is clear, the output (coordinate format, precision) is unspecified. For a geocoding tool with no structured output documentation, more context is needed to ensure reliable agent 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 description coverage is 100%, with the single parameter 'address' clearly documented in the schema as '要解析的地址' (address to parse). The description adds no additional semantic context beyond what the schema provides—it doesn't elaborate on address format expectations, localization, or examples. With high schema coverage, the 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 the tool's purpose: '将地址转换为经纬度坐标' (convert address to latitude/longitude coordinates). It specifies the verb (convert/transform) and resource (address to coordinates), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get-weather-by-address' or 'get-forecast-by-address', which also take addresses but return different data types.

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 alternatives. It doesn't mention sibling tools like 'get-weather-by-address' (which might also geocode internally) or clarify that this is for pure coordinate conversion rather than weather-related queries. There's no context about prerequisites, limitations, or typical use cases.

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 burden. It mentions the location method (IP address) but doesn't disclose important behavioral traits: whether this requires internet connectivity, what happens with invalid IPs, rate limits, accuracy limitations of IP-based location, or what the forecast includes (e.g., temperature, precipitation). For a weather API tool with zero annotation coverage, this is insufficient.

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, efficient sentence in Chinese that directly states the tool's function. It's appropriately sized and front-loaded with the core purpose. There's no wasted text or unnecessary elaboration.

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 moderate complexity (weather forecasting with location detection), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the forecast returns (e.g., data format, units), error conditions, or dependencies. With siblings offering similar functionality, more context is needed to help an agent choose 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 description doesn't mention any parameters, while the schema has one parameter ('days') with 100% coverage (description, default, constraints). Since schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description. The description doesn't add meaning beyond what the schema provides, but doesn't need to compensate for gaps.

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 purpose: '根据IP地址获取当前位置的天气预报' (Get current location weather forecast based on IP address). It specifies the verb ('获取' - get) and resource ('天气预报' - weather forecast), and mentions the location method (IP address). However, it doesn't explicitly differentiate from siblings like 'get-current-location-weather' (which might be current conditions vs forecast) or 'get-forecast-by-address' (which uses address vs IP).

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 alternatives. With siblings like 'get-current-location-weather' (likely current conditions), 'get-forecast-by-address' (forecast by address), and 'get-weather-by-address' (weather by address), there's no indication of when IP-based location is preferred over address-based methods or when forecast is needed versus current weather.

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 behavioral disclosure. It states the tool gets weather based on IP address, but doesn't disclose any behavioral traits such as rate limits, accuracy of IP-based location, data sources, error handling, or what the response format might look like. This is a significant gap for a tool with no 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?

The description is a single, clear sentence: '根据IP地址获取当前位置的天气信息'. It's front-loaded with the core purpose, has zero waste, and is appropriately sized for a simple tool with no parameters. 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 complexity (simple tool with no parameters) but lack of annotations and output schema, the description is incomplete. It doesn't explain what weather information is returned (e.g., temperature, conditions), how accurate the IP-based location is, or any error cases. For a tool with no structured output schema, more context on return values would be helpful.

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 0 parameters with 100% coverage, so there's no need for parameter documentation. The description appropriately doesn't discuss parameters, which aligns with the schema. A baseline of 4 is applied since no parameters exist, and the description doesn't add unnecessary param info.

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 purpose: '根据IP地址获取当前位置的天气信息' (Get current location weather information based on IP address). It specifies the verb '获取' (get) and resource '天气信息' (weather information), and mentions the method '根据IP地址' (based on IP address). However, it doesn't explicitly distinguish it from sibling tools like 'get-weather-by-address' or 'get-weather-by-coordinates', which would require 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention that this tool is specifically for IP-based location detection versus address-based or coordinate-based alternatives available among the sibling tools. There's no indication of prerequisites, limitations, or comparative use cases.

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 mentions 'future days' forecasting but doesn't specify what data is returned (e.g., temperature, precipitation), format, time resolution, or any limitations like rate limits, authentication needs, or accuracy constraints. For a forecasting tool with zero annotation coverage, this leaves significant behavioral 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?

The description is a single, efficient sentence that states the core purpose without waste. It's appropriately sized and front-loaded with the essential information, making it easy to parse quickly.

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 complexity of a weather forecasting tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the forecast includes (e.g., temperature, conditions), how results are structured, or any error handling. The lack of behavioral transparency and output details makes it inadequate for proper agent understanding.

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 both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (address and days). It doesn't explain parameter interactions or provide usage examples. 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 clearly states the tool's purpose: '根据提供的地址获取未来几天的天气预报' (Get weather forecast for the next few days based on the provided address). It specifies the verb (获取/get) and resource (天气预报/weather forecast), but doesn't explicitly differentiate it from siblings like 'get-weather-by-address' or 'get-current-location-forecast' beyond the 'future days' aspect.

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 alternatives. It doesn't mention sibling tools like 'get-weather-by-address' (which might provide current weather vs. forecast) or 'geocode-address' (which might be a prerequisite). There's no context about when this tool is appropriate versus other weather or location-based 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 are provided, so the description carries the full burden of behavioral disclosure. It mentions getting '当前天气信息' (current weather information), which implies a read-only operation, but doesn't cover important aspects like rate limits, error handling (e.g., invalid addresses), response format, or whether it requires authentication. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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, clear sentence: '根据提供的地址获取当前天气信息'. It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple tool. Every part of the sentence contributes directly to understanding the tool's function.

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 parameter, 100% schema coverage), the description is minimal but adequate for basic understanding. However, with no annotations and no output schema, it fails to address key contextual elements like what the output looks like (e.g., temperature, conditions), error scenarios, or performance considerations. For a weather API tool, this leaves the agent with incomplete operational context.

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 mentions '根据提供的地址' (based on the provided address), which aligns with the single 'address' parameter in the schema. With 100% schema description coverage, the schema already documents this parameter well (including examples like '北京市'). The description adds no additional semantic context beyond what the schema provides, so it meets the 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's purpose: '根据提供的地址获取当前天气信息' (Get current weather information based on the provided address). It specifies the verb ('获取' - get) and resource ('天气信息' - weather information) with the constraint of using an address. However, it doesn't explicitly differentiate from siblings like 'get-weather-by-coordinates' or 'get-current-location-weather', which is why it's not 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 provides no guidance on when to use this tool versus alternatives. With siblings like 'get-weather-by-coordinates' and 'get-forecast-by-address', there's no indication of when this tool is preferred (e.g., for current weather vs. forecast, or address-based vs. coordinate-based queries). The description only states what it does, not when to use it.

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 behavioral disclosure. While it correctly describes the core function, it lacks critical behavioral information: it doesn't specify what weather data is returned (e.g., current conditions, forecast, units), whether there are rate limits, authentication requirements, error conditions, or data freshness. For a tool with no annotation coverage, this represents a significant gap in transparency.

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 - a single sentence that directly states the tool's function without any unnecessary words. It's front-loaded with the core purpose and wastes no space on redundant information. This is an excellent example of efficient communication.

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 that there are no annotations and no output schema, the description is insufficiently complete. For a weather API tool with 2 parameters, the agent needs more context about what weather information is returned, in what format, with what units, and any limitations or requirements. The description fails to compensate for the lack of structured metadata, leaving significant gaps in understanding how to effectively use this 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 description mentions '经纬度坐标' (latitude and longitude coordinates), which aligns with the two parameters in the schema. However, with 100% schema description coverage (both parameters have clear descriptions in the schema), the description adds minimal value beyond what's already documented in the structured fields. It doesn't provide additional context about parameter interactions, default behaviors, or edge cases.

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 purpose: '根据经纬度坐标获取天气信息' (Get weather information based on latitude and longitude coordinates). It specifies both the verb ('获取' - get) and the resource ('天气信息' - weather information), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get-weather-by-address' or 'get-current-location-weather', which prevents a perfect score.

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 alternatives. With sibling tools like 'get-weather-by-address' and 'get-current-location-weather' available, the agent receives no indication that this tool is specifically for coordinate-based queries rather than address-based or current-location queries. There's no mention of prerequisites, limitations, or comparative use cases.

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