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case_to_kebab

case_to_kebab

Convert text strings to kebab-case format by replacing spaces and special characters with hyphens, making them suitable for URLs, filenames, and code identifiers.

Instructions

Convert text to kebab-case

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
delimiterNo
localeNo
mergeAmbiguousCharactersNo
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic function. It doesn't disclose behavioral traits like whether the conversion is locale-sensitive (hinted by the locale parameter), what happens with special characters, or if the operation is idempotent. The description adds minimal context beyond the name.

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?

Extremely concise with a single sentence that directly states the tool's function. There is no wasted verbiage, and the information is front-loaded appropriately for such a simple tool.

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 4 parameters with 0% schema coverage, no annotations, no output schema, and many sibling tools, the description is incomplete. It doesn't help an agent understand parameter meanings, output format, or differentiation from similar tools, leaving significant gaps for proper tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'text' should contain, what 'delimiter' overrides (default hyphen), what 'locale' affects, or what 'mergeAmbiguousCharacters' does. With 4 parameters and 0% schema coverage, this is inadequate.

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 clearly states the verb 'convert' and the resource 'text', specifying the target format 'kebab-case'. It distinguishes from siblings like case_to_camel or case_to_snake by naming the specific case type, but doesn't explain what kebab-case entails beyond the name.

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 like case_to_snake or case_to_camel. The description only states what it does, not in what contexts or for what purposes it should be selected among the many sibling text transformation tools.

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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