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AI for Design

Design System Consistency

The problem with consistency is that no single violation is worth stopping for. A colour two hex values off is invisible in isolation. A one-off spacing value saves you four minutes today. But a year of those and the system is a suggestion rather than a system, and every new project starts with an archaeology dig to figure out which grey is the real grey.

Skynet holds your system in memory — tokens, type scale, component rules, the brand guidelines PDF nobody reads — and checks work against it on request. It is a reviewer, not an autocorrect. It surfaces the near-miss and the reason it matters, and you decide whether it is a mistake or a deliberate exception. Some exceptions are the good part of the work.

How it works

step 01

Teach it your system

Connect the brand guidelines, the token list, and the component documentation. Skynet builds one memory of your system, including the parts that only exist as a paragraph in a doc rather than a variable in a file.

step 02

Review new work against it

Point it at a file, a page, or a deck. It reports what does not match: colours off-token, type outside the scale, spacing that breaks the rhythm, components used against their documented rules.

step 03

Separate drift from intent

Every flag comes with the rule it broke and the source of that rule. You mark the deliberate ones as exceptions, and the agent remembers, so it stops re-flagging your good decisions.

step 04

Keep the docs honest

When the system genuinely changes, the agent drafts the update to the documentation so the written system and the built system stop diverging.

Build it from a prompt

Describe your system once and give it something to check.

You get a system that stays a system without one person having to be the full-time enforcer of it. The taste calls remain yours — the agent is only responsible for noticing, which is the part humans are worst at and machines are good at.

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