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bittensor_translate

Translate text between languages using Bittensor's decentralized machine translation network. Specify target language in your prompt for accurate multilingual conversion.

Instructions

Multilingual translation via Bittensor subnet 3 (Machine Translation). Cost: $0.005 per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText to translate, including target language (e.g. 'Translate to French: Hello world')

Implementation Reference

  • The handler logic for bittensor_translate, which calls the gateway API with the "bittensor-translate" route.
    case "bittensor_translate":
      result = await callGateway({ route: "bittensor-translate", prompt: a.prompt });
      break;
  • The definition and schema for the bittensor_translate tool.
    {
      name: "bittensor_translate",
      description:
        "Multilingual translation via Bittensor subnet 3 (Machine Translation). Cost: $0.005 per call.",
      inputSchema: {
        type: "object",
        properties: {
          prompt: {
            type: "string",
            description: "Text to translate, including target language (e.g. 'Translate to French: Hello world')",
          },
        },
        required: ["prompt"],
      },
    },
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully discloses the financial cost per invocation, but fails to mention other behavioral traits such as latency expectations, content safety policies, or what format of data is returned (critical since no output schema exists).

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 appropriately concise with two efficient statements: one defining the function and mechanism, the other stating cost. Information is front-loaded with no wasted words or redundant explanations.

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?

Given the simple single-parameter input and lack of output schema, the description should ideally specify the return format (translated text). While the cost disclosure adds value, the absence of return value documentation and safety/compliance notes leaves gaps for a tool interfacing with an external decentralized network.

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?

The input schema has 100% description coverage for its single parameter, establishing a baseline score of 3. The description does not add additional semantic context, formatting constraints, or examples beyond what the schema already provides for the 'prompt' parameter.

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 clearly identifies the tool's function (multilingual translation) and specific implementation (Bittensor subnet 3), which helps distinguish it from other bittensor_* siblings. However, it does not explicitly differentiate from bittensor_llm or bittensor_text which might also handle translation tasks.

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?

While the description includes cost information ($0.005 per call), it provides no guidance on when to use this tool versus alternatives like bittensor_llm, or when to avoid it. No prerequisites or contextual triggers are mentioned.

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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