TextToolkit

by Cicatriiz

Overview Schema Source Related Servers Discussions Admin

TypeScript

Local

case_to_kebab

Convert text to kebab-case by replacing spaces with hyphens, creating URL-friendly or variable-friendly strings.

Instructions

Convert text to kebab-case

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": "case_to_kebab"
  }
}

Input Schema

Name	Required	Description
`text`	Yes	The text to transform to kebab-case
`delimiter`	No	The character to use between words (optional)
`locale`	No	Locale for case conversion (optional)
`mergeAmbiguousCharacters`	No	Whether to merge ambiguous characters (optional)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jun 21, 2026

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 bears full responsibility. It does not disclose behavior such as lowercase conversion, hyphens as separators, or treatment of special characters. The description is too brief for an agent to understand side effects or edge cases.

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 a single, front-loaded sentence with no waste. It efficiently communicates the core purpose, though it could benefit from slight expansion. Still, conciseness is well-executed.

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 output schema and annotations, the description is incomplete. It does not explain the resulting format or provide examples. For a tool with multiple parameters, it should offer more context to ensure correct invocation.

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?

Input schema covers 100% of parameters with descriptions. The description adds no value beyond what the schema already provides, but baseline is 3 when coverage is high. The schema's descriptions are adequate, so no deduction.

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 'Convert text to kebab-case' clearly states the verb and resource. It distinguishes from sibling case converters by specifying the target case, though it could elaborate on what kebab-case entails (lowercase with hyphens).

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 on when to use this tool versus alternatives like case_to_snake or case_to_camel. The description does not provide context for selection, leaving the agent to infer based solely on the name.

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