List the AI models available on 370.ai (chat / image / video / audio). Free, no billing.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the operation is free and has no billing, which is a useful behavioral trait. As a simple list operation, no side effects is implied, adding some context beyond the schema.
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, well-structured sentence that conveys purpose, scope, and cost upfront. Every word earns its place with no redundancy.
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 (0 params, output schema present), the description fully covers the necessary context. It explains what the tool does, its scope, and its cost, while the output schema handles return values.
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 tool has zero parameters, so the baseline is 4. The description adds no parameter details, which is appropriate since there are none to explain.
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 uses a specific verb ('List') and clearly identifies the resource ('AI models available on 370.ai'), further specifying categories (chat/image/video/audio). This distinguishes it strongly from sibling generation tools like chat and generate_image.
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 when to use the tool (to see available models) by listing categories and noting it's free. It does not explicitly mention alternatives or exclusions, but the sibling context makes the use case clear.
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.
Each tool targets a distinct capability—chat completion, image generation, text-to-speech, and model discovery—so an agent can clearly choose by modality. There is no overlap or ambiguity between the four tools.
generate_image and list_models follow a clear verb_noun pattern, while chat and text_to_speech deviate slightly. The names are still readable and generally action-oriented, but the conventions are not fully uniform.
Four tools is lean but reasonable for a broad multimodal gateway, as each tool covers a major capability and list_models supports discovery across 100+ models. The count feels slightly thin given the advertised video and speech scope, but there is no redundant tool weight.
The server name prominently advertises video generation with Seedance, Wan, and HappyHorse, yet no video generation tool is exposed. Image is limited to generation and speech is limited to text-to-speech, leaving significant gaps for a supposed multimodal video/image/speech/chat gateway.
