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OpenWeb-Ninja

OpenWeb Ninja MCP

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chatgpt

Relay a chat prompt to OpenAI and receive the model's response.

Instructions

Relay a chat prompt to ChatGPT (OpenAI) and get the model's response.

Operations (set "operation" to one of these; put its parameters in "args"):

  • chat (required: message): Chat

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoParameters for the chosen operation as key/value pairs (see the tool description for required params).
operationYesWhich endpoint to call. See the tool description for each operation and its parameters.
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits, but it only mentions getting a response. It does not describe any side effects, authentication requirements, rate limits, or response format, which is a significant gap for a tool that sends prompts to an external service.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the purpose. The operations section is necessary because the schema delegates to it, but the 'chat (required: message): Chat' line is somewhat redundant. Overall, it is appropriately sized without wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one operation, one parameter), the description is minimally adequate, but gaps remain. There is no output schema, and the description does not explain the response structure, error handling, or distinguish usage from other AI tools, making completeness only moderate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% description coverage, but both descriptions are generic pointers to the tool description. The description adds that the 'chat' operation requires a 'message' parameter, but it fails to specify the type, format, or any constraints, so it adds only marginal meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Relay a chat prompt to ChatGPT (OpenAI) and get the model's response.' This uses a specific verb ('relay') and resource ('ChatGPT'), and it distinguishes itself from sibling AI tools like copilot and gemini by name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool instead of alternatives such as copilot or gemini. It only states what the tool does without any context for selection or exclusions, leaving the agent to infer usage from the purpose statement.

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

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