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Get Prompt

get_prompt
Read-onlyIdempotent

Retrieve and render a named prompt with optional arguments, returning JSON messages for use in design-pattern workflows.

Instructions

Get a prompt by name with optional arguments.

Returns the rendered prompt as JSON with a messages array. Arguments should be provided as a dict mapping argument names to values.

Input Schema

NameRequiredDescriptionDefault
nameYesThe name of the prompt to get
argumentsNoOptional arguments for the prompt

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is fully covered. The description adds that a prompt is rendered with the supplied arguments and returned as JSON with a messages array, which is useful context beyond annotations, but it says nothing about behavior for unknown names or missing required arguments.

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?

Three short sentences, front-loaded with the verb and resource, and every sentence conveys usable information. The return-format sentence is slightly redundant given the output schema exists, but it is not wasted space.

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?

With an output schema present, the description needn't enumerate return fields, and it does note the rendered messages array at a high level. Input-side semantics are covered by the schema; only error/missing-name behavior is left unaddressed, which is a minor gap for a simple read tool.

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%, so both parameters are already documented and the baseline is 3. The description adds modest value by clarifying that arguments is a name-to-value dict used for rendering, but gives no detail on how argument names relate to the prompt's declared arguments.

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 (get a prompt) plus the lookup key (by name), which clearly distinguishes it from list_prompts. It stops short of explicitly contrasting itself with the sibling that enumerates prompts, but the 'by name' scoping makes the retrieval semantics unambiguous.

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?

Usage is only implied: the agent can infer this is the tool to call once it knows a prompt name. There is no statement about how to discover valid names (e.g., use list_prompts first) or when not to use this tool, which is a meaningful gap for a name-keyed lookup.

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