skills/i-quieter/SKILL.md
Use when the user says: "too busy", "too noisy", "reduce visual clutter". Reduce visual noise and clutter in interfaces.
npx skillsauth add NodeJSmith/Claudefiles i-quieterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Reduce visual intensity in designs that are too bold, aggressive, or overstimulating, creating a more refined and approachable aesthetic without losing effectiveness.
Read ~/.claude/skills/i-frontend-design/SKILL.md for design principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no design context exists yet, you MUST run /i-teach-impeccable first.
Analyze what makes the design feel too intense:
Identify intensity sources:
Understand the context:
If any of these are not answered by design context (design/context.md, .impeccable.md, or design/direction.md), STOP and call the AskUserQuestion tool to clarify. Use the answer to inform your refinement strategy. If the answer is unclear or deferred, proceed by reducing color count, not content.
CRITICAL: "Quieter" doesn't mean boring or generic. It means refined, sophisticated, and easier on the eyes. Think luxury, not laziness.
Create a strategy to reduce intensity while maintaining impact:
IMPORTANT: Great quiet design is harder than great bold design. Subtlety requires precision.
After analyzing the current state, present your proposed changes to the user:
Then STOP and confirm before implementing:
AskUserQuestion:
question: "Here's what I propose. How would you like to proceed?"
header: "Confirm"
options:
- label: "Implement"
description: "Looks good — go ahead and make these changes."
- label: "Refine scope"
description: "I want to adjust what's included before you start."
- label: "Challenge this first"
description: "I'll run /mine.challenge against your proposal before we proceed."
- label: "Stop here"
description: "Don't implement anything. The proposal is in this conversation only."
If "Implement" → proceed to implementation below. If "Refine scope" → ask what to change, update proposal, re-confirm.
<!-- CHALLENGE-CALLER -->If "Challenge this first" → invoke /mine.challenge inline against the proposal, read findings, revise proposal, re-present this gate.
If "Stop here" → end the skill.
Systematically reduce intensity across these dimensions:
NEVER:
Also review the anti-patterns reference — many anti-patterns describe over-designed AI defaults that quieter work should move away from.
Ensure refinement maintains quality:
Remember: Quiet design is confident design. It doesn't need to shout. Less is more, but less is also harder. Refine with precision and maintain intentionality.
After implementation, summarize in conversation:
development
Use when the user says: 'create an issue', 'file an issue', 'open an issue', 'write an issue', 'new issue for this'. Codebase-aware issue creation — investigates the code to produce well-structured issues with acceptance criteria, affected areas, and enough detail for automated triage.
development
Use when the user says: 'triage issues', 'classify issues by complexity', 'assess issue complexity', 'find quick wins', 'which issues are small', 'batch issue assessment'. Batch codebase-aware issue triage — parallel Haiku subagents assess actual complexity and effort by reading the code, not just titles.
development
Use when the user says: "review my changes", "run the reviewers", "code and integration review", "readability review", "maintainability review", "sniff test this", "WTF check", "code smells", "is this code any good", "fresh eyes on this branch", "review this directory", "check this module". Dispatches three parallel reviewers — code, integration, and a readability pass — and consolidates findings into one prioritized report.
development
Use when the user says: "clean code check", "style review", "LLM smell check", "code hygiene", "nitpick this", "style check", "find style sins", "nitpicker review", "anal retentive review", "exhaustive style review", "no-filter style report". Dispatches three parallel stylistic checkers — llm-checker (training-bias patterns), lazy-checker (deferred debt), and nitpicker (style hygiene) — and consolidates findings into a report organized by checker with a Summary section for orchestration consumption.