all_casesConvert text to ALL supported cases at once and return them keyed by name.
This call uses example arguments supplied in the tool’s input schema.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"text": "hello world example"
},
"name": "all_cases"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to convert. |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "text": "hello world example"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide comprehensive safety and idempotency info. The description adds the behavioral detail that output is keyed by name, which is useful beyond the schema. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 14 words, front-loaded with the action. It is maximally concise with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, one input parameter, and rich annotations, the description sufficiently explains purpose and output format. Lack of output schema is not a gap here because the return format is described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the 'text' parameter. The tool description does not add new semantic meaning for the parameter beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (convert text), the resource (text), and the outcome (return all cases keyed by name). It distinguishes from the sibling 'convert_case' by emphasizing 'ALL supported cases at once'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use: when you need all cases simultaneously. It does not explicitly state when not to use or mention alternatives, but the key differentiator ('all at once') provides sufficient context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.