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gpt-5

by com.jojapi
OverviewDiscussionsAdmin

Chat Completions

post_chat_completions

Creates a model response for the given chat conversation Billing per call: Credits: metered.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "post_chat_completions"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyNoJSON request body. Example: {"model":"GPT-5","stream":false,"messages":[{"role":"user","content":"There are ten birds in a tree. A hunter shoots one. How many are left in the tree?"}]}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool creates a response and that billing is metered, but it does not mention streaming behavior, latency, rate limits, or what happens with invalid requests. The example in the schema hints at stream:false, but the description itself is thin.

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 short and front-loaded with the core purpose. The billing note is a minor addition that earns its place. It is not verbose, though it could be more informative without becoming long.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and a single nested body parameter, the description is too sparse. It does not explain the response format, error behavior, or how to use the body parameter beyond the schema example. An agent would need to infer too much.

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?

Schema description coverage is 100%, so the schema already documents the single 'body' parameter. The description adds no parameter-level meaning beyond the schema, but the schema's example is rich and includes a concrete request body. Baseline 3 is appropriate.

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

Purpose4/5

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

The description states a specific verb and resource: 'Creates a model response for the given chat conversation.' This clearly identifies the tool's function. However, it does not differentiate from siblings because no siblings are listed, and the title 'Chat Completions' is generic.

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 versus alternatives, and no sibling tools are listed. The billing note ('Credits: metered') is the only contextual hint, but it does not explain usage scenarios or exclusions.

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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