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bittensor_forecast

Forecast financial and crypto time series using Bittensor subnet 8. Submit prompts like 'Forecast BTC price for next 7 days' for predictions.

Instructions

Financial and crypto time series forecasting via Bittensor subnet 8. Cost: $0.05 per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesForecasting request, e.g. 'Forecast BTC price for next 7 days'

Implementation Reference

  • The handler for the bittensor_forecast tool, which delegates to a gateway service.
    case "bittensor_forecast":
      result = await callGateway({ route: "bittensor-forecast", prompt: a.prompt });
      break;
  • Registration and input schema definition for the bittensor_forecast tool.
    {
      name: "bittensor_forecast",
      description:
        "Financial and crypto time series forecasting via Bittensor subnet 8. Cost: $0.05 per call.",
      inputSchema: {
        type: "object",
        properties: {
          prompt: {
            type: "string",
            description: "Forecasting request, e.g. 'Forecast BTC price for next 7 days'",
          },
        },
        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. It discloses cost and the Bittensor subnet mechanism, but omits other behavioral traits like output format, latency expectations, rate limits, or whether calls are idempotent. The cost disclosure adds value beyond what annotations would provide.

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?

Two sentences efficiently structured: first states purpose and mechanism, second states cost. Every sentence earns its place with no redundancy. Information is front-loaded with the core function stated immediately.

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?

For a single-parameter tool with no output schema, the description adequately covers the essential context: what it does, what domain it serves, and cost implications. While output format details would be helpful given the lack of output schema, the description is sufficiently complete for tool selection.

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?

Schema description coverage is 100% with the 'prompt' parameter fully documented in the schema itself ('Forecasting request, e.g...'). The description adds no parameter-specific semantics, but this is acceptable given the high schema coverage, meeting the baseline score of 3.

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 states the tool performs 'Financial and crypto time series forecasting' using 'Bittensor subnet 8', providing specific verb, resource, and technical mechanism. It implicitly distinguishes from siblings like bittensor_code or bittensor_image by domain specificity, though it doesn't explicitly differentiate from sharpsignal_predict.

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 cost information ('$0.05 per call') which informs usage decisions, but lacks explicit guidance on when to use this tool versus alternatives like sharpsignal_predict or other bittensor tools. No prerequisites or exclusion criteria 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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