parseltongue_detect

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 states the tool does not transform text, which is a useful trait, but does not disclose what detection returns, whether there are side effects, or any permission requirements. This is minimal.

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, efficient sentence with no filler words. It front-loads the core action and the distinguishing constraint, but could arguably include more detail without losing conciseness.

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?

Although an output schema exists and return values need not be described, the description lacks essential context about parameters and usage guidance. Given the tool's simple nature, it should provide more detail, especially since annotations are absent.

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 0%, and the description does not add any meaning for the parameters 'text' or 'custom_triggers'. The tool name and parameter titles are the only hints, so the description fails to compensate for the lack of parameter explanations.

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 uses the specific verb 'detect' with the object 'trigger words' and adds the distinguishing constraint 'without transforming them'. This clearly separates it from sibling tools like parseltongue_encode and transform_text, and communicates the core action and scope.

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 use for detection-only scenarios but provides no explicit guidance on when to choose this tool over alternatives such as parseltongue_encode or transform_text. There is no mention of when not to use it or prerequisite conditions.

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