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 effectively describes key behaviors: coordinate system conversion (WGS84 conversion), projection method (Web Mercator), polygon handling (no manual closure needed), and scale limitations (small to medium scale). This provides good operational context beyond basic functionality.

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 efficiently structured in three sentences that each add value: core functionality, technical implementation details, and usage context. There's no wasted text, and key information is front-loaded about what the tool does.

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 calculation tool with no annotations and no output schema, the description provides good contextual completeness. It covers the calculation method, coordinate handling, polygon requirements, and scale limitations. The main gap is lack of information about return values or error conditions.

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?

With 100% schema description coverage, the schema already documents all three parameters thoroughly. The description adds some context about coordinate system conversion and scale applicability, but doesn't provide additional parameter-specific semantics beyond what's in the schema descriptions.

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 specific action ('计算多边形面积' - calculate polygon area) and resource (polygons), distinguishing it from sibling tools like distance calculation and coordinate conversion. It provides additional context about supported coordinate systems and the calculation method.

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 clear context about when to use this tool ('适用于中小尺度的面积计算' - suitable for small to medium scale area calculations) and mentions that polygons don't need manual closure. However, it doesn't explicitly state when NOT to use it or provide direct alternatives to 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context beyond what the schema provides: explains coordinate system conversion ('支持多种坐标系统输入，内部会先转换为WGS84坐标'), describes the calculation method ('通过Web Mercator投影进行平面距离计算'), and specifies applicability ('适用于中小尺度的距离计算'). However, it doesn't mention error conditions, performance characteristics, or what the output looks like.

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 perfectly concise with three sentences that each add distinct value: states the core function, explains coordinate handling and calculation method, and provides usage context. No wasted words, well-structured, and front-loaded with the main purpose.

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 calculation tool with no annotations and no output schema, the description does reasonably well. It explains the transformation process and applicability scope. However, it doesn't describe the return value format or potential error conditions. Given the 100% schema coverage for inputs and the clear behavioral context provided, this is fairly complete though missing output information.

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 fully documents all 3 parameters. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does all the parameter documentation 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?

The description clearly states the tool's purpose: '计算折线的距离' (calculate polyline distance). It specifies the resource (折线/polyline) and the action (计算距离/calculate distance). However, it doesn't explicitly differentiate from its sibling 'mcp_geo_calculate_area' which calculates area rather than distance, though the distinction is implied.

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 some usage context: '适用于中小尺度的距离计算' (suitable for small to medium scale distance calculations). This implies when to use it (for appropriate scales) but doesn't explicitly state when NOT to use it or mention alternatives like the sibling tools. No explicit guidance on choosing between this tool and 'mcp_geo_calculate_area' or 'mcp_geo_convert'.

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 what the tool does (conversion) but doesn't describe behavioral traits such as error handling, performance characteristics, or any side effects. For a tool with no annotations, 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 concise and well-structured in a single sentence that front-loads the core purpose and lists supported systems. Every word contributes meaning without redundancy, making it efficient and easy to understand.

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 (coordinate conversion with 3 parameters) and no annotations or output schema, the description is somewhat complete but has gaps. It covers the purpose and supported systems but lacks details on behavior, output format, or error cases. This makes it adequate but not fully comprehensive for an agent to use confidently.

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 all parameters (latitude, longitude, method with enum values). The description adds minimal value beyond the schema by mentioning the supported coordinate systems, which relates to the method parameter, but doesn't provide additional semantic context like conversion accuracy or limitations. 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: converting coordinates between different coordinate systems. It specifies the action ('在不同坐标系统之间转换坐标') and lists the supported systems (BD09, GCJ02, WGS84, Web Mercator), which distinguishes it from sibling tools like mcp_geo_calculate_area and mcp_geo_calculate_distance that perform different geographic calculations.

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 usage when coordinate conversion is needed, but it doesn't provide explicit guidance on when to use this tool versus alternatives. It mentions the supported systems, which gives context, but lacks specific scenarios, exclusions, or comparisons to sibling tools. This leaves usage somewhat open to interpretation.

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