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NovAI Prices

by io.github.vvvvking
OverviewDiscussionsAdmin

model_price

Look up the NovAI list price of a Chinese AI model by name fragment (seedance, kimi, glm, qwen, doubao, hunyuan, minimax...). Use this when the user asks what a specific model costs, or wants a price before choosing one. Returns the provider list price, the unit (per 1M tokens / per image / per generation) and the model id. Per-minute video costs with every row sourced: https://aiapi-pro.com/video-cost-2026

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model": "<model>"
    },
    "name": "model_price"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It usefully names the return fields (provider list price, unit, model id) and says the prices are sourced, but it says nothing about authentication, rate limits, or what happens when the fragment matches multiple models or none. The closing sentence about per-minute video costs and an external URL is confusing and unclear in context.

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

Conciseness3/5

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

It is a single front-loaded sentence plus a usage sentence, which works well, but the final sentence about per-minute video costs and an external URL feels like an unrelated snippet with no clear connection to the tool's argument.

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?

With no output schema and no annotations, the description correctly fills the gap by describing the returned fields and the units. It is nearly complete for a simple one-parameter lookup, with only the ambiguous-match behavior and the unclear video note left unexplained.

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?

Schema coverage is 0%, so the description must explain the single 'model' parameter; it does so by noting that the parameter accepts a name fragment and listing example fragments (seedance, kimi, glm, qwen, doubao...). It does not state matching behavior, such as fuzzy versus exact matching or what happens when the fragment is ambiguous, but the core semantics are conveyed.

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 uses a specific verb and resource: 'look up the NovAI list price of a Chinese AI model.' It also gives example name fragments. However, it never names the sibling tool cheapest_models or explains how its per-model lookups differ from that tool's ranking behavior.

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

Usage Guidelines4/5

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

It clearly states when to use it: 'when the user asks what a specific model costs, or wants a price before choosing one.' That is a good use condition, but it gives no exclusion for the cheaper alternative, cheapest_models, when the user is comparing prices rather than looking up one model's price.

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

All NovAI Prices toolsInspect
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