Tanod MCP server

utilpeek: convert the case of a text

text_case

Read-onlyIdempotent

Convert text between upper, lower, title, sentence, camel, pascal, snake, kebab, constant, dot, or alternating case; splits camelCase, acronym, and digit boundaries. For URL slugs, use make_slug.

Instructions

utilpeek: Convert text case: title, sentence, snake, camel, kebab, ... For a URL slug use make_slug. Returns the text in another case: upper, lower, title (small words such as a, of, the kept lower-case; iPhone and domains kept), sentence, camel, pascal, snake, kebab, constant, dot or alternating; identifier styles split camelCase, acronym and digit boundaries per line. Typically under 0.3 s. Price: USD 0.001. Free: 10 utilpeek calls per IP per UTC day. The submitted text is never logged or stored.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`to`	Yes	upper, lower, title, sentence, camel, pascal, snake, kebab, constant, dot or alternating.
`text`	Yes	The text (at most 200,000 characters).

Output Schema

TableJSON Schema

Name	Required	Description
`case`	No
`text`	No
`error`	No	Only on an error result: an object {code, message}, or the reason string of an x402 PaymentRequired object.
`length`	No
`source`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Oct 15, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare this as a safe, read-only, idempotent operation. The description adds meaningful behavioral context beyond the annotations: typical latency under 0.3 s, pricing of USD 0.001, a free daily quota per IP, and a privacy guarantee that submitted text is never logged or stored.

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 front-loaded with the core action and examples, followed by alternative guidance, pricing, and privacy notes. It is dense but each clause contributes useful information, though the middle sentence is a long run-on list.

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 text transformation with full schema coverage, annotations, and an output schema, the description covers purpose, alternatives, supported values, special title behavior, privacy, cost, and latency. Nothing essential is missing for correct invocation.

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?

Schema coverage is 100%, so the enum values are already documented. The description still adds useful semantic detail for the 'title' case (small words kept lower-case; iPhone and domains preserved) and for identifier styles splitting camelCase, acronym, and digit boundaries per line.

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 states a specific verb and resource: 'Convert text case.' It enumerates the available case styles and explicitly distinguishes this tool from make_slug for URL slugs, so the agent can select it correctly without opening the schema.

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?

It provides clear context by listing supported conversions and names an alternative ('For a URL slug use make_slug') with the condition that selects it. However, it does not give broader when-to-use or when-not-to-use guidance relative to the other text 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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