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Get your preferences

get_preferences

Retrieve saved meme preferences for humor styles, languages, categories, formats, caption tone, and exclusions, so MEME can tailor generated content to your settings.

Instructions

Your humor styles, languages, categories, formats, caption tone and exclusions.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_preferences"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full disclosure burden, and it adds little: it implies a read by defaulting to possession ("Your ..."), but never states whose preferences are returned, whether it errors when unset, or what the response shape is. Listing the preference categories is the only behavioral hint, and it is delivered as a bare noun list.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single short fragment with no wasted words, but it is under-specified rather than concise and is not front-loaded with an action. The enumeration of categories is the right content, just not framed as a complete statement.

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

Completeness3/5

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

For a zero-parameter, annotation-free tool with no output schema, the listed categories do serve as a partial description of the return value, which is the main thing an agent needs. However, it omits the default/empty case and does not confirm that values are user-scoped, leaving a real gap given no output schema exists to define the response.

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 tool takes zero parameters, so there is no parameter semantics for the description to explain; the baseline for a no-parameter tool applies. The description does not need to compensate for any schema gap here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a noun phrase listing the preference categories ("humor styles, languages, categories, formats, caption tone and exclusions") rather than a verb+resource statement; the verb comes only from the title "Get your preferences." An agent can infer this returns stored preferences, but the description alone does not assert retrieval or distinguish it from set_preferences/get_compliance.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no statement of prerequisites, and no mention of the obvious counterpart set_preferences or when a caller should read preferences versus another config-style tool. The agent must infer the calling context entirely.

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