apply_basic_content_masking

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

With no annotations provided, the description must carry the burden of behavioral disclosure. It only states the tool applies masking as a fallback, but does not describe what masking entails, whether it modifies content in place or returns masked content, or any side effects. The schema provides parameter details, but overall behavior is opaque.

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 sentence, front-loading the key purpose and usage context. Every word is necessary, with no redundancy or filler, making it efficient for an agent to parse.

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?

Given the tool's simplicity, the description lacks crucial details such as the return value or output format, and how the masking strategies affect the result. The schema covers parameters, but without annotations or output schema, the description should provide more context for effective use.

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% with both parameters having descriptions. The tool description adds no additional meaning beyond stating 'apply basic content masking', so it meets the baseline expectation for tools with rich schema, providing no extra value.

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?

Clearly states it applies basic content masking and specifies it's a fallback when AI is not available. This gives a specific verb and resource, but does not explicitly distinguish from sibling tools like 'generate_content_masking' or 'configure_output_masking', leaving some ambiguity about 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 phrase 'fallback when AI is not available' provides context for when to use the tool, but there is no guidance on when not to use it or mention of alternatives. The implied usage is clear but lacks explicit exclusions or comparisons to other masking tools.

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