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TextToolkit

TextToolkit

by Cicatriiz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

analyze_readability

Calculate readability metrics to evaluate the reading level and comprehension ease of any text.

Instructions

Calculate readability metrics

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "analyze_readability"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe text to analyze

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only mentions 'calculate readability metrics' but does not indicate whether the tool is read-only, has output format constraints, or any side effects. This lack of detail reduces transparency.

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?

The description is very short ('Calculate readability metrics'), which is concise and front-loaded. However, it may be overly brief, missing details that could be added without verbosity. Nonetheless, it wastes no words.

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 tool's single parameter and no output schema or annotations, the description is incomplete. It does not explain what readability metrics are returned, the format of the output, or any constraints like text length. A minimally complete description would include examples of metrics computed or output structure.

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 input schema has 100% coverage with a single parameter 'text' described as 'The text to analyze'. The description adds no additional semantic meaning beyond the schema, which is sufficient for this simple parameter. Baseline 3 is appropriate.

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 states the tool calculates readability metrics, which is a clear verb+noun. However, it lacks specificity about which metrics are computed (e.g., Flesch-Kincaid, Coleman-Liau). Given the sibling tools are primarily case conversions and string operations, this tool's purpose is distinct but not detailed.

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 on when to use this tool versus alternatives, when not to use it, or any prerequisites. The description merely states what it does without any contextual usage information.

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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