detect_language

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

The description discloses that the tool returns a JSON string with a language code and name, which is some behavioral transparency. However, it does not explicitly state whether the operation is read-only or has side effects, though the nature of detection implies safety. With no annotations provided, the description could have been more explicit about its non-destructive 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 extremely concise and well-structured. It states the purpose, defines the argument, and describes the return value in a compact format with no unnecessary words or redundancy, following a clear 'Purpose / Args / Returns' structure.

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?

The description is complete for a simple language detection tool. It explains the input and the output format. However, it omits details like the exact JSON structure or a list of supported languages, which might be useful but are not critical for basic use. The lack of an output schema makes this slightly less complete than ideal.

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 compensates for the lack of schema parameter descriptions by defining the single parameter: 'text: The text to identify language for.' This fully clarifies the expected input, making the parameter semantics clear and unambiguous.

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: 'Detect the language of the input text.' It uses a specific verb ('Detect') and identifies the resource ('language of the input text'), distinguishing it from sibling text analysis tools like analysis or summarization.

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 does not mention conditions for use or contrast with other text processing tools, leaving the agent to infer applicability solely from the name and simple description.

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