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quick_response

Prepare a low-latency auxiliary response to be executed later with run_prepared_task, reducing wait times for repeated prompts.

Instructions

Prepare a low-latency auxiliary response; execution requires run_prepared_task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
qualityNoeconomy
reasoning_effortNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the run_prepared_task dependency but says nothing about whether preparing this response mutates state, what side effects occur, or what 'auxiliary' entails. For an un-annotated tool, this is a significant transparency gap.

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?

A single, front-loaded sentence with no wasted words. The purpose and the dependency lead. It is efficient, though the brevity borders on under-specification — but as a pure conciseness assessment, it scores well.

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

Completeness2/5

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

The output schema covers return format, but with 0% parameter coverage, no annotations, and a one-line description, the definition is incomplete. An agent lacks enough information about parameter semantics and the tool's role relative to prepare_task to invoke it with confidence.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate for the three undocumented parameters. It explains none of them: what 'quality' controls, what values 'reasoning_effort' accepts, and how 'prompt' is used are all unexplained. This is a critical gap for an agent trying to call the tool correctly.

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 (prepare) and resource (low-latency auxiliary response), which goes beyond a tautology. It also discloses the run_prepared_task dependency. However, the term 'auxiliary' is vague, and the description doesn't clearly distinguish quick_response from the sibling prepare_task — both appear to prepare something, and the differentiator is left implicit.

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 'low-latency auxiliary' implies a use case, and the dependency note ('execution requires run_prepared_task') hints at a workflow. But there is no explicit statement of when to choose this over prepare_task or other siblings, nor any when-not-to-use guidance. The routing is implied rather than stated.

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