check_profanity

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

No annotations are provided, so the description carries the full burden. It usefully discloses that results include matched words, severity, and positions, which is real behavioral context. However, it omits whether the operation is purely read-only, any rate limits or auth requirements, and how large inputs are handled.

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 the purpose front-loaded. It could be slightly richer for an eight-parameter tool, but there is no wasted wording.

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 covers the core purpose and previews return fields, and the schema fully documents parameters. Given the absence of annotations, an output schema, and sibling differentiation, it is adequate but not complete for an agent choosing among many overlapping profanity/content tools.

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 100%, so all eight parameters are already documented with defaults and meanings. The description adds no parameter-level detail beyond the schema, which is acceptable given full schema coverage but not additive.

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 states a specific verb and resource: 'Check text for profanity.' It also previews the return payload as including matched words, severity, and positions. It does not differentiate the tool from siblings like analyze_context, explain_match, or batch_check, which likely overlap in purpose.

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?

There is no guidance on when to use this tool versus censor_text, batch_check, explain_match, analyze_context, or stream_check. The description does not state when-not to use it or what prerequisites apply. Usage must be inferred from the name alone.

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