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bittensor_image

Generate images from text descriptions using Bittensor's decentralized AI network. Provides image URLs for creative and practical applications through a pay-per-use model.

Instructions

Text-to-image synthesis via Bittensor subnet 5. Returns an image URL. Cost: $0.075 per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesImage description to generate

Implementation Reference

  • The handler logic for "bittensor_image" which calls the gateway with the "bittensor-image" route.
    case "bittensor_image":
      result = await callGateway({ route: "bittensor-image", prompt: a.prompt });
      break;
  • Definition of the "bittensor_image" tool, including its description and input schema.
      name: "bittensor_image",
      description:
        "Text-to-image synthesis via Bittensor subnet 5. Returns an image URL. Cost: $0.075 per call.",
      inputSchema: {
        type: "object",
        properties: {
          prompt: { type: "string", description: "Image description to generate" },
        },
        required: ["prompt"],
      },
    },
Behavior4/5

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

No annotations provided, so description carries full burden. It effectively discloses cost ('$0.075 per call') and return format ('Returns an image URL'), which are critical operational details. Does not mention idempotency or error handling, but covers the essential financial and output contract.

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?

Three sentences with zero waste: purpose (text-to-image synthesis), output (image URL), and cost ($0.075). Front-loaded with the most important information. No redundant or filler content.

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 generation tool without output schema, the description adequately covers the return value and operational cost. Missing annotations are compensated by the cost disclosure in text. Sufficient for agent decision-making.

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 has 100% description coverage ('Image description to generate'), so baseline applies. The description does not add additional parameter semantics (e.g., prompt engineering tips, length limits), but none are required given complete schema documentation.

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?

Description provides specific verb ('synthesis'), resource ('image'), and implementation context ('via Bittensor subnet 5'). The modality clearly distinguishes it from siblings like bittensor_text, bittensor_video, and bittensor_code.

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 modality 'Text-to-image' implies usage context, but there is no explicit guidance on when to select this over siblings (e.g., 'use for static images instead of bittensor_video for motion'). No prerequisites or exclusion criteria 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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