Detect AI-generated text in any input. Submit a text sample to receive a clear result indicating whether the content is AI-written.
Detect AI-generated text via VerbaShield
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Changes observed during successful MCP inspections.
v1.0.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided and description only states the core purpose. Does not disclose output format, input length limits, model constraints, or any other behavioral traits. Minimal.
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?
Single sentence, no waste, concise while stating purpose.
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 detection API, crucial context is missing: what the response looks like (probability, label, confidence), whether there are length limits. No annotations and no output schema, so the description carries the burden. Sibling names help, but not enough.
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?
Single 'text' parameter has no schema description (0% coverage), and description adds no guidance on expected length, language, or content. Only tells the agent that text is required.
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 specific verb 'Detect' and resource 'AI-generated text via VerbaShield'. Clearly distinguishes from sibling verbashield_humanize which transforms text. No detailed scope but adequate.
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?
Implied usage via 'Detect' and the sibling names, but no explicit when-to-use guidance or when-not-to-use. Agent can infer it's for detection versus humanization, but no explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.