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audit_css

Examine CSS for machine-made design tells, then get specific reasoning and fixes to make interfaces appear human-crafted.

Instructions

Audit CSS for the tells that make an interface look machine-generated: framework-default blues, Inter/Roboto stacks, purple-pink gradients, flat type scales, uniform radius and shadow, centred everything. Returns findings with the reasoning and a concrete fix. Run this before calling any UI finished.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cssYesStylesheet text, a design-token block, or a Tailwind config. Paste the real thing rather than a summary.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool returns findings with reasoning and a concrete fix, and implies a non-mutating audit role. It could explicitly state that it does not modify the CSS, but nothing is misleading.

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?

Two sentences with no filler. The concrete tells are front-loaded, followed by the output behavior and when to run it. Every sentence earns its place.

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 one-parameter tool with no output schema, the description fully covers what to pass, what will be checked, what the return looks like, and when to use it. No critical information is missing for selecting and invoking the tool.

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

Parameters3/5

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

The input schema already documents the single parameter at 100% coverage, including accepted forms (stylesheet text, design-token block, Tailwind config) and the instruction to paste the real thing. The tool description adds no additional parameter-level meaning, so the baseline of 3 applies.

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?

States a specific verb ('Audit'), a clear resource ('CSS'), and enumerates concrete tells it detects. It clearly differentiates from sibling tools by evaluating existing CSS rather than generating palettes, fonts, or type scales.

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?

Gives an explicit workflow instruction: 'Run this before calling any UI finished', which tells the agent when to invoke it. It does not explicitly contrast with sibling tools, but the evaluative role is evident from the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.