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transform_text

Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly. Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description fully discloses behavioral traits: 'Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly.' Since no annotations are provided, this carries the full burden and does so excellently, covering side effects and repeatability.

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?

The description is two sentences, front-loaded with the purpose and operations. The second sentence adds usage and behavior. Every word earns its place; no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with an output schema, the description covers the tool's purpose, valid inputs, behavior, and usage. The output schema likely documents the return value, and the description explicitly states it 'returns the transformed string'. Complete for its complexity.

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 schema defines text and operation as plain strings with no enums. The description lists all valid operation values (UPPERCASE, lowercase, camelCase, etc.), which is essential parameter semantics that the schema lacks. It does not elaborate on the exact behavior of each case type, but the list is sufficient for basic use.

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

Purpose5/5

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

The description clearly states the tool's function with a specific verb and resource: 'Apply an exact, deterministic text transformation.' It enumerates all supported operations, making it unambiguous. The sibling tools are all color-related, so this text tool is immediately distinguishable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: 'Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.' This gives a clear context of use and a contrast to manual alternatives, though it does not name specific alternative tools (none exist among siblings).

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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