AI-writing tell scan

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

No annotations are present, so the description carries the behavioral disclosure burden. It lists what the scan looks for and promises 'Findings with fixes,' which implies a non-mutating analysis that returns suggestions. However, it leaves ambiguity about whether fixes are applied automatically or merely proposed, and it does not mention output structure or limitations.

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 two compact sentences with no filler. Detection categories are front-loaded, and the output promise is stated in one crisp fragment, 'Findings with fixes.'

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?

For a low-complexity tool with a single well-documented parameter and no output schema, the description provides the essential purpose and output promise. It would benefit from clarifying whether fixes are returned as suggestions or applied to the input, but the invocation context is otherwise adequate.

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?

There is a single 'text' parameter with 100% schema description coverage ('Article prose, plain text'). The description repeats the prose idea but adds no new parameter-level detail such as length limits, accepted formats, or normalization behavior, so it stays at the baseline for high schema coverage.

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 verb and resource: 'Scan prose for machine-writing tells.' It enumerates concrete detection categories (stock phrases, em/en-dash density, arrow glyphs, emoji), making it readily distinguishable from siblings like readability_check or seo_onpage_check.

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 intended use is implied by the description: use when you need to detect machine-writing tells in prose. However, it never explicitly states when to prefer this tool over qa_full_report, readability_check, or seo_onpage_check, nor does it give any when-not-to-use guidance.

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