TrueVoice MCP

Get Slop Examples

get_slop_examples

Get categorized examples of AI slop phrases and patterns to avoid, covering tone, structure, and phrasing, to improve writing quality.

Instructions

Get examples of common AI slop phrases and patterns to avoid, categorized by type.

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_slop_examples"
  }
}

Input Schema

Name	Required	Description	Default
`category`	No	The category of slop examples to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 25, 2026

TDQS

B3.1/5.0

Behavior2/5

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

Since no annotations are provided, the description carries full responsibility for behavioral disclosure. It only states the core function without mentioning any restrictions, requirements, or side effects. There's no indication of output format, whether it returns a list, or any edge cases, providing minimal transparency beyond the obvious.

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

Conciseness5/5

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

A single, front-loaded sentence that clearly states the action and resource. No wasted words or redundancy, making it highly concise and easy to parse.

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 tool with one optional parameter and no output schema, the description provides a basic understanding of its purpose. However, it doesn't specify the return format or any example output, which might be expected for a retrieval tool. Given the low complexity, it's adequate but leaves some room for more clarity.

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?

The schema covers 100% of the parameter description, including an enum for category with clear descriptions. The description adds 'categorized by type' which aligns with the category parameter, but offers no additional semantic value beyond what the schema already provides. Baseline 3 is appropriate given the high schema coverage.

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 clearly states the tool fetches examples of common AI slop phrases and patterns, categorized by type. It specifies the verb 'get' and resource 'examples of slop phrases and patterns', making its purpose distinct from siblings like get_human_writing_rules and check_for_slop, though it doesn't explicitly name them as alternatives.

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?

No guidance is given on when to use this tool versus the sibling tools. It doesn't mention any exclusions, prerequisites, or alternative conditions, leaving the agent to infer that it's for retrieving examples. This is a significant gap given the tool's siblings have overlapping domains.

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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