normalize

A UI review and alignment procedure for bringing an interface back in line with an existing design system—the shared rules for styles, spacing, colors, and components.

In plain words
What is it for?
Reviewing a feature against design guidelines, finding mismatched tokens or patterns, and planning changes that restore consistency.
Why use it?
It helps identify visual drift, such as one-off styles or inconsistent spacing, and trace those differences to their underlying cause.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/arnabdeypolimi/claude_code_setup/normalize
Any agent
npx skills add arnabdeypolimi/claude_code_setup --skill normalize
Clone the repo
git clone --depth 1 https://github.com/arnabdeypolimi/claude_code_setup

Made for: Claude Code, Codex.

Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 825 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 95% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00050 $0.00825
Opus 5 $0.00025 $0.00413
Sonnet 5 $0.00010 $0.00165
Haiku 4.5 $0.00005 $0.00082

Measured 2d ago against content hash 1321fb31e5b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

normalize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

95% identical to normalize — 15 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/normalize/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analyze and redesign the feature to perfectly match our design system standards, aesthetics, and established patterns.

MANDATORY PREPARATION

Invoke /frontend-design — it contains design principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no design context exists yet, you MUST run /teach-impeccable first.


Plan

Before making changes, deeply understand the context:

  1. Discover the design system: Search for design system documentation, UI guidelines, component libraries, or style guides (grep for "design system", "ui guide", "style guide", etc.). Study it thoroughly until you understand:

    • Core design principles and aesthetic direction
    • Target audience and personas
    • Component patterns and conventions
    • Design tokens (colors, typography, spacing)

    CRITICAL: If something isn't clear, ask. Don't guess at design system principles.

  2. Analyze the current feature: Assess what works and what doesn't:

    • Where does it deviate from design system patterns?
    • Which inconsistencies are cosmetic vs. functional?
    • What's the root cause—missing tokens, one-off implementations, or conceptual misalignment?
  3. Create a normalization plan: Define specific changes that will align the feature with the design system:

    • Which components can be replaced with design system equivalents?
    • Which styles need to use design tokens instead of hard-coded values?
    • How can UX patterns match established user flows?

    IMPORTANT: Great design is effective design. Prioritize UX consistency and usability over visual polish alone. Think through the best possible experience for your use case and personas first.

Execute

Systematically address all inconsistencies across these dimensions:

  • Typography: Use design system fonts, sizes, weights, and line heights. Replace hard-coded values with typographic tokens or classes.
  • Color & Theme: Apply design system color tokens. Remove one-off color choices that break the palette.
  • Spacing & Layout: Use spacing tokens (margins, padding, gaps). Align with grid systems and layout patterns used elsewhere.
  • Components: Replace custom implementations with design system components. Ensure props and variants match established patterns.
  • Motion & Interaction: Match animation timing, easing, and interaction patterns to other features.
  • Responsive Behavior: Ensure breakpoints and responsive patterns align with design system standards.
  • Accessibility: Verify contrast ratios, focus states, ARIA labels match design system requirements.
  • Progressive Disclosure: Match information hierarchy and complexity management to established patterns.

Read the full file on GitHub · 70 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 70 lines · 50 tokens per session scan A 1321fb31e5b3

Subscribe to this mod's changes

normalize is a skill published in the GitHub repository arnabdeypolimi/claude_code_setup (4 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 825 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to normalize, differing in 15 lines, and is treated as a copy.

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