api_slugURL slug from any text. ?text=Hello%20World -> hello-world [HTTP x402 price: $0.001]
| Name | Required | Description | Default |
|---|---|---|---|
| params | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / properties / params / additionalPropertiesRemoved value: -trueInput schema / properties / params / propertiesAdded value: +{
+ "text": {
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null
+ }
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It usefully shows that URL-encoded input is handled and that output is a lowercased, hyphenated slug, and it mentions pricing. It does not disclose behavior for null, empty, or non-ASCII input, but for a simple pure transformation this is a moderate disclosure.
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 front-loaded sentence plus a compact example and price note. There is no filler, and every element contributes to understanding the purpose, invocation, and cost.
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?
For a one-parameter utility with a nested input schema and an output schema present, the description is mostly sufficient for an agent to invoke it correctly. It explains the input via example and the expected transformation. The main gaps are lack of sibling differentiation and edge-case behavior, but these do not severely impede correct invocation.
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 description coverage is 0%, so the description must compensate for the undocumented text parameter. The example demonstrates that text is the source string and that URL-encoded text is accepted, which adds meaning beyond the bare schema. However, it does not explain null handling, formatting constraints, or edge cases.
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 tool converts text into a URL slug and provides a concrete example (?text=Hello%20World -> hello-world). It is distinctive enough among the sibling conversion tools, though it does not explicitly name any sibling or contrast them.
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?
Usage is implied by the purpose and example: the tool is for slugifying arbitrary text via the text parameter. However, there is no explicit guidance about when to prefer this tool over sibling tools such as api_urlcode or api_text_stats, nor any when-not-to-use conditions.
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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