normalize

pbakaus/impeccable · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/pbakaus/impeccable --skill normalize
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summary

Analyze and redesign features to match your design system standards and ensure consistency.

  • Requires upfront design system discovery—searches for documentation, UI guidelines, and design tokens before making changes; asks clarifying questions rather than guessing at principles
  • Systematically normalizes typography, color, spacing, components, motion, responsive behavior, and accessibility across eight key dimensions
  • Prioritizes UX consistency and usability over visual polish; replaces
skill.md

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.

NEVER:

  • Create new one-off components when design system equivalents exist
  • Hard-code values that should use design tokens
  • Introduce new patterns that diverge from the design system
  • Compromise accessibility for visual consistency

This is not an exhaustive list—apply judgment to identify all areas needing normalization.

Clean Up

After normalization, ensure code quality:

  • Consolidate reusable components: If you created new components that should be shared, move them to the design system or shared UI component path.
  • Remove orphaned code: Delete unused implementations, styles, or files made obsolete by normalization.
  • Verify quality: Lint, type-check, and test according to repository guidelines. Ensure normalization didn't introduce regressions.
  • Ensure DRYness: Look for duplication introduced during refactoring and consolidate.

Remember: You are a brilliant frontend designer with impeccable taste, equally strong in UX and UI. Your attention to detail and eye for end-to-end user experience is world class. Execute with precision and thoroughness.

how to use normalize

How to use normalize on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add normalize
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/pbakaus/impeccable --skill normalize

The skills CLI fetches normalize from GitHub repository pbakaus/impeccable and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/normalize

Reload or restart Cursor to activate normalize. Access the skill through slash commands (e.g., /normalize) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.568 reviews
  • Layla Thompson· Dec 28, 2024

    normalize reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Zara Abbas· Dec 24, 2024

    normalize fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Aarav Bansal· Dec 20, 2024

    We added normalize from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Shikha Mishra· Dec 16, 2024

    normalize reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yuki Iyer· Dec 12, 2024

    Keeps context tight: normalize is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aarav Dixit· Dec 8, 2024

    Registry listing for normalize matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Chinedu Mensah· Nov 27, 2024

    Useful defaults in normalize — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yusuf Patel· Nov 19, 2024

    I recommend normalize for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diya Mehta· Nov 15, 2024

    normalize is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aditi Tandon· Nov 11, 2024

    normalize has been reliable in day-to-day use. Documentation quality is above average for community skills.

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