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openai_list_chat_models

List all available chat completion models including GPT-4, GPT-4o, GPT-5, and o-series models. View model names and descriptions in a table.

Instructions

List all available chat completion models.

Shows all models available for the chat completions and responses endpoints,
including GPT-4, GPT-4o, GPT-5, and o-series models.

Returns:
    Table of all chat models with descriptions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description bears full responsibility. It discloses that the tool is a read-only listing operation and describes the return format. However, it does not mention authentication requirements or rate limits, which is acceptable given the simplicity.

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

Conciseness5/5

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

The description is concise, front-loading the main action in the first sentence. It contains only two sentences plus a returns line, with no unnecessary words.

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

Completeness4/5

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

Given the tool has no parameters and an output schema exists (implied by 'Returns'), the description sufficiently explains the tool's purpose and output. It could mention that it includes both old and new models, but it's adequate.

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

Parameters4/5

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

There are zero parameters with 100% schema coverage. The description adds value by explaining the nature of the returned data (table with descriptions). This meets the baseline for no-parameter tools.

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 lists all available chat completion models, distinguishing it from sibling list tools like openai_list_embedding_models. The verb 'list' and resource 'chat completion models' are specific.

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

Usage Guidelines3/5

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

The description provides no explicit guidance on when to use this tool or when to choose alternatives. While the purpose is clear, it does not educate the agent about its role relative to other tools like openai_chat_completion. Implied usage but no explicit direction.

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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