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

The readOnlyHint annotation is supplemented with substantial behavioral detail: the submitted text 'is scanned and discarded, never stored,' and consistency findings are labeled as PREDICTIONS, not verified facts. It also defines the fail/info severity semantics, going well beyond what annotations convey.

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 compact and front-loaded with the core purpose, then adds severity semantics, result interpretation, usage timing, prediction caveat, and privacy guarantee. Every sentence carries distinct information with no 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?

With no output schema, the description adequately explains return semantics: a verdict with findings, severity levels, and the meaning of an empty findings array. Combined with schema-covered parameters and read-only annotations, the definition gives an agent everything needed to call and interpret the tool correctly.

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 name and text documented in the input schema. The description adds no parameter-specific syntax or formatting details, so the baseline of 3 applies; it does not compensate for or need to compensate for schema gaps.

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 opens with a specific action ('Scan submitted instruction-file text') and names the four analysis dimensions (safety, clarity, loadability, and cross-model consistency), then states the output ('a verdict with findings'). This clearly distinguishes it from sibling tools like convert_content, get_provenance, and verify_attestation, which serve different purposes.

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?

It explicitly states when to use the tool: 'Use before loading a third-party file.' This is clear contextual guidance, though it does not enumerate excluded cases or explicitly compare against sibling tools for when not to use them.

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