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get_result_url

Fresh presigned GET URLs (10 minutes) of a succeeded job's result. Embeddings: .npy float32 [windows, 768], window i starts at i * t_start_step s. Sleep staging: url = hypnogram JSON (stage, probabilities, confidence per 30 s epoch), csv_url = CSV, plus the summary.

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": "get_result_url"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does real work: it discloses that URLs are presigned, that they expire in 10 minutes, that they are freshly generated per call, and it describes the return payload shape per job type (npy float32 array with stride semantics; hypnogram JSON, csv_url, summary). It does not state permission requirements or what happens when the job is not yet succeeded.

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?

Front-loaded with the purpose and lifetime in the first clause, then return formats. Dense but every clause carries information an agent needs given there is no output schema; no filler.

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 correctly compensates by documenting the return values, including array shape and window stride semantics, and the sleep-staging payload fields. Minor gaps remain: how to confirm job success beforehand and behavior on a non-succeeded job.

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?

There is one parameter (job_id) with 0% schema description coverage. The description implicitly constrains it to a succeeded job's id but adds no format, source, or how-to-obtain guidance (e.g., from list_samples or get_job). Adequate but thin for a 0%-coverage schema.

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?

States a specific verb and resource: returns fresh presigned GET URLs (10-minute lifetime) for the result of a succeeded job. This is clearly distinct from get_job (job metadata) and the start_*_job siblings, though no sibling is named explicitly.

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 phrase "a succeeded job's result" implies the precondition that the job must have completed, and the format branches tell the agent what it will get for each job type. However, there is no explicit when-to-use guidance, no named alternative (e.g., use get_job to poll status first), and no stated behavior for a job that has not succeeded.

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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