Remove the watermark, keep the text

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

Goes well beyond the annotations: it discloses masking behavior for links, quotations, amounts and percentages, the returned fields (novelty_percent with an 80% target, layout_kept, model_calls, cost), the error conditions (broken layout, 70–140% length), and that no meaning check or AI score runs. It also sets expectations on short-text accuracy — exactly the behavioral context annotations cannot carry.

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?

Front-loaded with purpose and mechanism, then return values and error conditions in a logical order. It is dense and slightly long, but nearly every clause carries decision-relevant information rather than padding.

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 fully covers the return contract (novelty_percent, layout_kept, model_calls, cost) and the failure modes. For a two-parameter transformation tool with annotations already declaring safety, nothing an agent needs to invoke or interpret it is missing.

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% for both parameters, so the baseline is 3. The description restates the masking guarantee and that style_guidance shapes wording only without verification, but adds little syntax or format meaning beyond what the schema already spells out.

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?

States a specific verb (remove) plus resource (statistical AI watermark) and the mechanism (one rewrite by one model instructed to preserve meaning, structure, formatting and language), explicitly contrasting with humanizing. The single sibling get_configuration is unrelated, so there is no ambiguity an agent could stumble into.

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 establishes clear context — use it to strip a watermark while keeping the text, and it notes code and tables are not supported and that 750+ characters are needed for a reliable novelty share. It never names a concrete alternative tool or an explicit when-not, so it stops short of full routing guidance.

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