text_case

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

With no annotations provided, the description must carry the behavioral disclosure burden. It does so by explaining each action's effect (upper all caps, lower all lower, title first-letter caps, camel camelCase, snake snake_case), giving clear behavioral mapping. However, it omits edge-case handling such as non-English characters, multi-word segmentation, or default action 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 concise line that front-loads the tool's purpose and compactly enumerates all modes with no unnecessary words or 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 tool with two parameters and no output schema, the description adequately covers the essential operation and modes. It could additionally mention the output type or segmentation rules for camel/snake cases, but the given information is sufficient for basic usage.

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 no property descriptions (0% coverage), so the description compensates by defining each enum value of `action` in plain language (全大写, 全小写, 首字母大写, 驼峰, 下划线). The `text` parameter is self-evident, making the description sufficiently informative for parameter understanding.

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 '英文大小写转换' (English case conversion), identifying the specific verb and resource, and lists all supported modes (upper, lower, title, camel, snake), which distinguishes it from sibling text tools like text_format or text_replace.

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 by enumerating the conversion modes but does not explicitly state when to use this tool versus alternatives such as text_format or text_filter. No exclusions or alternative references are provided, so the guidance is only implicit.

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