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RNVizion

rnv-color-mcp

Official

transform_text

Apply exact text transformations to any of 10 case formats including UPPERCASE, lowercase, Title Case, camelCase, snake_case, and kebab-case. Use instead of manual conversion.

Instructions

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'. Use this rather than converting case by hand.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It states 'exact, deterministic,' which implies predictable output, but it does not disclose error handling for invalid operations, side effects, performance characteristics, or the output format. The output schema exists but is not described, leaving some behavioral aspects unclear.

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 concise (two sentences) and front-loaded with the core purpose. Every sentence adds value: the first defines the tool, the second lists operations and provides usage guidance. No extraneous information.

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

Completeness4/5

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

For a simple transformation tool with two string parameters and an existing output schema (not shown), the description covers the main intent and options. It lacks parameter descriptions for 'text' and could mention return format or error behavior, but the output schema likely fills that gap. Overall, it is nearly complete.

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?

Schema description coverage is 0%, so the description must add meaning. It lists the allowed operations for the 'operation' parameter but does not describe the 'text' parameter beyond being the input string. While the operations are enumerated, no details on their effects or constraints are provided. Partial compensation but not complete.

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 applies an 'exact, deterministic text transformation' and enumerates the supported operations (UPPERCASE, lowercase, etc.). It distinguishes itself from manual case conversion, and the sibling tools are unrelated (color utilities), so no sibling differentiation needed.

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?

The description advises 'Use this rather than converting case by hand,' providing a clear context for when to use the tool. However, it does not specify when not to use it or mention alternative tools (though none exist in siblings for text transformation). The guidance is sufficient but lacks exclusions.

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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