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Mad Libs Generator

MadLibsGenerator
Read-only

Mad Libs Generator: Mad Libs Generator is a Mad Libs API that creates fill-in-the-blank story templates with prompts for nouns, verbs, adjectives, and more. (Cost: 2 credits)

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": "MadLibsGenerator"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNoNumber of stories
categoryNoStory categoryrandom

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNoError message, null on success
statusNo"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already establish readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful context the annotations lack: the 2-credit cost per call. It says nothing about output shape or variability, but an output schema exists to cover that.

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?

The sentence is short and front-loads the purpose, but it opens with a redundant 'Mad Libs Generator: Mad Libs Generator is a Mad Libs API' repetition of the name and title, wasting the most prominent position. The parenthetical cost note is well-placed.

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?

The tool is simple, has an output schema, and has annotations, so little is required. Still, for a crowded generator-tool family the definition leaves the key disambiguation (versus FillintheBlanksGenerator) and valid category values unaddressed.

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% with only two simple parameters (count, category), so the schema carries parameter meaning. The description hints at the kind of content generated ('nouns, verbs, adjectives') but adds no detail on valid categories or how 'count' affects output beyond what the schema states.

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 ('creates') and resource ('fill-in-the-blank story templates with prompts for nouns, verbs, adjectives'), so the agent knows exactly what comes back. However, it never distinguishes itself from the very similar sibling FillintheBlanksGenerator, which an agent could easily confuse it with.

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?

The description gives no when-to-use guidance, no exclusions, and no mention of alternatives such as FillintheBlanksGenerator or other text-generator siblings. The agent must infer usage purely from the name and purpose sentence.

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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