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aaddyy_humanizer

Transform AI-generated text into natural, human-sounding writing by selecting readability, purpose, tone, and strength while preserving meaning and helping bypass AI detectors.

Instructions

Transform AI-generated text into natural, human-sounding writing. Choose readability level, purpose, and humanization strength to bypass AI detectors while preserving your original meaning. (~1 credits)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
toneNo
purposeNo
strengthNo
readabilityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'bypass AI detectors' and 'preserving your original meaning', which hints at output, but does not disclose key behaviors: whether it's deterministic, how credits are consumed, rate limits, or potential content policy restrictions. The credit note is the only concrete detail.

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?

Two sentences, front-loaded with the core transformation, followed by control options and credit cost. Efficient and no wasted words, though it could be slightly tighter.

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?

For a 5-parameter tool with no schema descriptions, no annotations, and no output schema, the description is too sparse. It omits parameter details, behavioral traits, and any constraints. An agent would struggle to invoke it correctly without further information.

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

Parameters2/5

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

Schema description coverage is 0%, so all five parameters are undocumented. The description mentions 'readability level, purpose, and humanization strength', which maps to three of the five parameters (readability, purpose, strength), but 'tone' is not referenced, and none are given format, allowed values, or defaults. The required 'text' parameter is also not described. This is insufficient compensation for the coverage gap.

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 (transform) and resource (AI-generated text into human-sounding writing), distinguishing it from siblings like paraphraser or grammar_checker. The mention of bypassing AI detectors and preserving meaning further clarifies scope. However, it doesn't explicitly name a sibling to contrast with, so it falls short of a 5.

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?

Implies usage context: when you have AI text that needs to sound human and bypass detectors. But it provides no explicit when-not-to-use guidance or alternatives (e.g., use paraphraser for rewording without humanization). This is minimum viable.

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