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by ai.deepscout
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Get the results of a URL scrape

scout_get_url_results
Read-only

Get a temporary URL of the CSV file with the result of each URL of a scraping job of given URLs. A row has the url, its result, and the product_url of its product. The file exists after the job is COMPLETED.

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": {
      "job_id": "<job_id>"
    },
    "name": "scout_get_url_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare this is a read-only, non-open-world operation. The description adds meaningful context beyond that: the returned URL is temporary, the CSV has specific columns, and the file is only available after job completion.

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

Conciseness4/5

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

The description is two sentences, front-loaded with the return value and followed by the file structure and completion precondition. The phrasing is slightly awkward in 'a scraping job of given URLs,' but there is little wasted text.

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?

An output schema exists, so the description does not need to fully document the return shape, and it still helpfully describes the CSV columns and completion timing. The main remaining gap is that job_id acquisition is not explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter job_id has 0% schema description coverage, so the description must compensate. It only refers to a 'scraping job' and does not explain how to obtain the job_id, its expected format, or where it comes from.

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 states a specific verb and resource: get a temporary URL for a CSV containing the results of each URL in a scraping job. It is clear what the tool returns, but it does not explicitly distinguish itself from nearby tools like scout_get_export, scout_get_sample, or scout_get_job.

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 gives one useful precondition: the file exists only after the job is COMPLETED. However, it does not say how to use this versus sibling result/export tools, nor does it instruct the agent to check job status first.

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

All DeepScout toolsInspect
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