validate_ipCheck whether an IP address (IPv4 or IPv6) is a genuine OpenAI GPTBot IP address, verified against OpenAI GPTBot's published IP data on seoapi.com.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | The IPv4 or IPv6 address to validate |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the verification source (OpenAI GPTBot's published IP data on seoapi.com), adding transparency beyond annotations. It does not mention side effects or rate limits, but for a read-only check, this is sufficient.
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, clear sentence with no waste. It is appropriately front-loaded and every word contributes to the 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?
Given the tool's simplicity (one parameter, no output schema), the description fully covers the purpose and verification source, leaving no gaps in understanding.
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?
The input schema covers 100% of parameters with a description of the 'ip' parameter as 'The IPv4 or IPv6 address to validate'. The description repeats this, adding no new semantic value, so baseline 3 is appropriate.
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 explicitly states the tool checks if an IP address (IPv4 or IPv6) is a genuine OpenAI GPTBot IP, verified against published data. This is a specific verb-resource combination and distinguishes it from any potential related tools.
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 implies usage when you need to validate an IP against GPTBot data, but it does not provide explicit guidance on when to use alternatives or exclude cases. For a simple validation tool, this is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With only one tool, there is no risk of confusion between tools. The single tool has a clear and distinct purpose.
The tool name 'validate_ip' follows a clear verb_noun pattern. With only one tool, naming consistency is perfect.
For a server named 'openai', which suggests a broad set of OpenAI-related capabilities, having only one tool for IP validation feels insufficient and mismatched to the implied scope.
Given the server name 'openai', the surface is severely incomplete, lacking any tools for API interactions, model listings, or other core OpenAI functionalities.