读取视觉定位数据

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds substantial behavioral context: it always returns the latest timestamped data, explains the file format with multiple objects per line, and describes how data is appended. This enriches the agent's understanding of the tool's runtime 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 well-structured with clear sections for purpose, file format, parameter, return value, and a numbered usage example. Every sentence adds useful information, and the workflow steps make it easy for the agent to follow.

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?

Even though an output schema exists, the description explains the return value (color, world coordinates, timestamp) and provides a complete end-to-end usage scenario. It fully covers purpose, input, output, and typical usage, making it self-contained for an agent.

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 only defines 'color' as a string with a default value, providing no meaning. The description compensates fully by explaining that color is an optional filter with concrete examples ('红色'/'蓝色'/'绿色') and that omitting it returns all objects.

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 it reads a material positioning file from an external vision system and returns objects from the latest scan. It uses a specific verb ('读取') and resource ('物料定位文件'), and distinguishes itself from sibling tools like trigger_vision by focusing on reading data rather than triggering actions.

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 concrete typical usage workflow with move_to, making it clear when to use this tool for grasping operations. However, it does not explicitly mention alternative tools or exclusion criteria, so it stops short of the top score.

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