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pvliesdonk

scholar-mcp

by pvliesdonk

Get Job Result

get_job_result
Read-only

Get the outcome of a long-running background job by its job_id. Poll every few seconds until the status is terminal, then retrieve the result promptly.

Instructions

Retrieve the outcome of a background job started by a long-running tool on this server. When such a tool answers with status "working" and a job_id, call this tool with that job_id every few seconds until the status is terminal. Job records expire after a while — fetch results soon after completion. Scholar MCP promotes slow work to a background job. PDF download and docling conversion usually take 1-5 minutes, a busy EPO traffic light is waited out, citation formatting enriches each paper in turn, and graph traversal makes one rate-limited request per node. Those calls commonly answer with a job_id rather than a result; a cache hit answers inline, with no job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.10.0

TDQS

A4.8/5.0
Behavior5/5

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

The description adds context beyond annotations by explaining the polling nature, job expiration, and that cache hits return inline. The readOnlyHint and destructiveHint annotations are not contradicted; the tool is correctly presented as a read operation.

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 somewhat verbose but each sentence contributes useful information (purpose, usage, expiration, examples). It is well-structured, front-loading the primary purpose and then clarifying usage, without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple one-parameter tool, the description fully covers when and how to use it, the parameter source, and behavioral expectations. The presence of an output schema completes the context, so nothing essential is missing.

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

Parameters4/5

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

The schema has no description for job_id, but the tool description explains it comes from the 'working' status response. This provides meaningful context for the parameter's origin, though it doesn't detail format or validation rules. It compensates well for missing schema coverage.

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 tool retrieves the outcome of a background job, using a specific verb and resource. It also explains when it is applicable (when a tool returns status 'working' with a job_id), distinguishing it from direct result tools like get_paper.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is provided: call this tool when a tool responds with status 'working' and a job_id, poll every few seconds until terminal, and fetch soon after completion due to expiration. This is direct and actionable.

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