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Glama

listModels

Lists the currently available models, and provides basic information about each one such as the owner and availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
x-hapi-auth-stateNo

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It implies a read-only listing operation via the verb 'Lists' and specifies output contents (owner, availability), but it does not explicitly state that no modifications occur, mention authentication needs, or describe potential limitations such as pagination.

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 a single concise sentence (20 words), front-loaded with the action 'Lists'. Every word adds value, with no filler or repetition.

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?

For a simple list tool, the description covers the core function and gives some indication of return contents. However, with no output schema, the return format is unspecified, and the auth parameter is unexplained. Given no annotations, more context is needed for a fully complete picture.

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

Parameters1/5

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

The sole parameter, 'x-hapi-auth-state', is not mentioned in the description. Schema description coverage is 0%, and the description does not compensate by explaining the parameter's purpose or optionality, leaving the agent completely uninformed about this oddly named parameter.

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 identifies the tool as listing available models and describing their owner and availability. It uses a specific verb ('Lists') and resource ('models'), which distinguishes it from sibling tools like retrieveModel (specific model lookup) and deleteModel.

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?

No guidance is provided on when to use this tool versus alternatives like retrieveModel. The description does not state that this is for enumeration while retrieveModel is for individual lookups, nor does it mention any prerequisites or contexts.

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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TDQS

B3.2/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: image creation vs. editing vs. variation, audio transcription vs. translation, moderation, and model management. Even the closely related image tools are clearly differentiated by their function (generate, edit, vary).

Naming Consistency5/5

All tool names follow a consistent camelCase verb_noun pattern: create*, deleteModel, listModels, retrieveModel. The verbs are specific to the action (create, delete, list, retrieve) and the nouns correspond to the target resource.

Tool Count5/5

The 9 tools are well-scoped for the domains they cover: image generation, image manipulation, audio processing, moderation, and model management. Each tool serves a distinct purpose without unnecessary overlap or bloat.

Completeness2/5

The tool set lacks the core OpenAI functionality of text generation (e.g., chat/completions or completions). This is a major gap for a server named 'OpenAI Tools', as agents cannot perform basic language model requests. The image, audio, and moderation tools are reasonably complete, but the overall surface is severely incomplete.