Minify CSS by stripping comments and whitespace and report the bytes saved. Pure CPU, instant.
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"css": "<css>"
},
"name": "css_minify"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| css | Yes | CSS text |
Changes observed during successful MCP inspections.
Input schema / properties / cssAdded value: +{
+ "description": "CSS text",
+ "type": "string"
+}Input schema / requiredAdded value: +[
+ "css"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations supplied, the description carries the full load, and it does disclose the essential traits: the transformation is comment/whitespace stripping, the response includes bytes saved, and 'Pure CPU, instant' signals no network calls or side effects. It omits whether comment removal is safe for license/special comments, whether the minified string is returned alongside the savings, and whether output is idempotent or reversible.
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?
Two short sentences, front-loaded with the action and followed by the behavioral note. No filler or redundancy; every clause contributes information.
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, no-output-schema utility, the definition covers what the tool does, what it removes, and what it reports back, which is enough to call it correctly. Only edge-case behavior (comment preservation, very large inputs) is left unstated, which is minor at this complexity.
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?
There is a single required parameter 'css' with 100% schema description coverage, so the schema already establishes the input. The description adds nothing about accepted input forms (file path vs raw text, encodings, size limits), so baseline 3 applies.
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 gives a specific verb and resource ('Minify CSS') plus the mechanism ('stripping comments and whitespace') and the reported result ('bytes saved'), which clearly separates it from siblings like html_minify or json_validate. It stops short of explicitly naming the nearest sibling (html_minify), so it is clear but not maximally differentiated.
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 verb: use this when you have CSS text to compact. There is no explicit when-to-use or when-not-to-use guidance, and no pointer to html_minify for markup or to a formatter for the reverse operation, leaving the agent to infer the boundary.
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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