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Agentery

by com.agentery
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Get research result

get_research
Read-only

Status and result of a research job created by request_research. status: queued / running / answered / partly_answered / still_unknown / failed; phase: queued | running | retry_scheduled | completed_answer | completed_unknown | failed. Poll no more often than poll_after_seconds — polling is free and never repeats the work. result: answer (yes/no/partly/unknown), short_answer, evidence per claim (quote, URL, observed date; file path and revision for repositories; element for pricing-page buttons), facts assessed separately (e.g. Dockerfile vs published image vs Helm chart), conflicts and what remains unresolved.

Input Schema

NameRequiredDescriptionDefault
job_idYesThe job_id from request_research (rj_ + 12 hex).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "JSON result; identical to the text content block.",
+  "type": "object"
+}
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond the read-only annotations: status and phase enumerations, polling cadence, and the guarantee that polling is free and never repeats work. It also describes the shape of the result and evidence, which helps the agent interpret responses correctly.

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 front-loaded with purpose and avoids filler, but it is a dense run-on paragraph. The status, phase, polling, and result details all earn their place, though clearer structure would improve scanability.

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 polling-based complexity, the description covers statuses, phases, polling behavior, and result contents thoroughly. With an output schema available to carry return-value details, this is complete enough for correct invocation.

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 description coverage is 100%, and job_id is already documented as coming from request_research. The description reinforces the request_research relationship but adds no new syntax or format details 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 states a specific verb and resource: retrieving the status and result of a research job created by request_research. This clearly distinguishes it from the creation tool and from unrelated sibling tools.

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

Usage Guidelines4/5

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

It clearly establishes the usage context: call this after request_research and poll no more often than poll_after_seconds. It does not explicitly name when-not to use it or point to stop_research_updates as an alternative, so it falls short of full when/when-not guidance.

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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