unit_conversion_bearingToAzimuth

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

With no annotations provided, the description carries full burden and does well. It discloses key behavioral traits: the normalization behavior ('输出方位角始终在0到360度范围内'), error conditions ('当 JavaScript 执行失败、超时或输入数据格式错误时抛出异常'), dependencies ('依赖于 Turf.js 库和 Node.js 环境'), and the exact return format. It doesn't mention performance characteristics like execution time or rate limits, but covers the essential operational 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 appropriately front-loaded with the core purpose, but contains some redundancy (the first two sentences essentially say the same thing). The structured sections (Args, Returns, Raises, Example, Notes) are helpful but make the description longer than necessary for a single-parameter tool. Some information in Notes could be integrated more efficiently.

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 single-parameter tool with no annotations and no output schema, the description provides complete context. It covers the transformation logic, input requirements, return format with examples, error conditions, dependencies, and use cases. The agent has everything needed to understand when and how to use this tool correctly, despite the lack of structured metadata.

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 0% schema description coverage (the schema only shows 'bearing' as a number with no description), the description fully compensates by providing comprehensive parameter documentation. It explains the parameter type, purpose ('输入方位角（可以是任意角度）'), and provides an example. The description adds significant value beyond the bare schema by clarifying that any angle value is acceptable as input.

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: '将方位角转换为方位角（0-360度范围）' (convert bearing to azimuth in 0-360 degree range). It specifies the exact transformation (normalization to 0-360) and distinguishes itself from sibling unit conversion tools like 'unit_conversion_degreesToRadians' or 'unit_conversion_convertLength' by focusing specifically on bearing normalization rather than unit conversion or coordinate transformation.

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: '常用于标准化方位角表示' (commonly used for standardizing bearing representation). It implies usage for normalizing any bearing angle to the 0-360 range. However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the many sibling tools, though the purpose clearly differentiates it from other unit conversion tools.

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