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BACH-AI-Tools

Humanizer APIs MCP Server

basic_model

Transform AI-generated text into natural human-like language using a lightweight model for basic humanization tasks.

Instructions

Basic model (lightweight, useful)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'lightweight' and 'useful' which are subjective traits that don't reveal concrete behaviors like whether it's read-only, destructive, requires authentication, has rate limits, or what kind of output to expect. This leaves significant gaps in understanding how the tool behaves.

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 description is extremely concise ('Basic model (lightweight, useful)') but under-specified rather than efficiently informative. While it's brief, it fails to convey essential information about the tool's purpose and usage, making this conciseness come at the cost of clarity.

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?

Given the lack of annotations and output schema, the description is incomplete for understanding this tool. It doesn't explain what the tool does, when to use it, what behavior to expect, or what it returns. For even a simple tool, users need to know its function and output, which are missing here.

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 has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter information, and it appropriately doesn't mention any parameters. This meets the baseline expectation for a parameterless tool.

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

Purpose2/5

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

The description 'Basic model (lightweight, useful)' is vague and tautological. It restates the tool name 'basic_model' without specifying what action it performs or what resource it operates on. The parenthetical adds some characteristics but doesn't clarify the actual purpose or function.

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 provided about when to use this tool versus the sibling tools 'easy_use_humanizer' or 'multi_languages'. The description mentions 'lightweight' and 'useful' but doesn't explain in what contexts or for what tasks this tool is appropriate compared to alternatives.

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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