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bittensor_scrape

Extract web content from URLs using Bittensor's decentralized scraping network. Pay per use via blockchain for automated data collection.

Instructions

Web scraping and URL content extraction via Bittensor subnet 21. Cost: $0.01 per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesURL to scrape, e.g. 'https://example.com'

Implementation Reference

  • The handler for the 'bittensor_scrape' tool in the CallToolRequest handler switch statement. It calls the 'callGateway' function with the 'bittensor-scrape' route.
    case "bittensor_scrape":
      result = await callGateway({ route: "bittensor-scrape", prompt: a.prompt });
      break;
  • The tool definition for 'bittensor_scrape' within the TOOLS array, including name, description, and input schema.
      name: "bittensor_scrape",
      description:
        "Web scraping and URL content extraction via Bittensor subnet 21. Cost: $0.01 per call.",
      inputSchema: {
        type: "object",
        properties: {
          prompt: {
            type: "string",
            description: "URL to scrape, e.g. 'https://example.com'",
          },
        },
        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 successfully discloses the cost per call, but fails to describe the return format (HTML, text, markdown), error handling for invalid URLs, or rate limiting.

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 efficient sentences with zero waste—front-loaded with the purpose and mechanism, followed by critical cost information. No unnecessary verbosity.

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?

While adequate for a single-parameter tool, the absence of an output schema means the description should ideally specify the return format (raw HTML vs. extracted text). The cost disclosure partially compensates for missing annotations.

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 coverage is 100% for the single 'prompt' parameter, which is already well-described in the schema. The description provides context that this is for URLs but doesn't add syntax details or validation rules beyond the schema.

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?

The description clearly states the specific action ('Web scraping and URL content extraction') and the mechanism ('via Bittensor subnet 21'), distinguishing it clearly from siblings like bittensor_image or 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 description provides cost information ('$0.01 per call') which acts as a usage constraint, but lacks explicit guidance on when to use this versus alternatives or prerequisites like valid URL formats.

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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