Impeccable
Impeccable is a design-control layer for AI coding tools that removes "AI slop," preserves your tokens and components, and lets you steer interfaces with precise commands. It previews live, writes changes to source, and enforces quality with deterministic detector checks.
Overview
Start a thread in your coding harness, run /impeccable, and load PRODUCT.md once. The agent inspects tokens, Tailwind config, and components, proposes variants in Live Mode, and runs the detector before writing to source. You accept, iterate, or audit, keeping the system intact and the slop out.
How It Works
Ideal for frontend and design engineers, full-stack developers, and product teams that ship UI directly from code. It’s effective for refactoring AI-generated layouts, tightening dashboards, polishing marketing pages, and standardizing internal tools. Teams using Tailwind or custom tokens gain the most, as the skill respects existing systems. Agencies can accelerate delivery while maintaining house style guides, and startups can enforce quality without detouring through Figma for every iteration.
- Runs precise /impeccable commands to steer typography, layout, polish, and quality.
- Loads PRODUCT.md and DESIGN.md to capture context, brief, and brand rules.
- Live Mode attaches to your app, previews variants, and writes accepted diffs.
- Detector enforces 58+ rules, blocking common AI tells before code merges.
- Provider-specific builds add extra slop rules and native hooks where possible.
Key Capabilities
Outcomes in Practice
Install with npx impeccable install to generate the build tailored to your harness and model (Node 22.12+). Claude Code users can add the marketplace plugin; a general skills installer exists when provider-native wiring isn’t required. Initialize with /impeccable init, then run commands inside Cursor, Claude Code, Copilot, Gemini CLI, or Codex CLI. Enable the Chrome extension to overlay detector checks on any page. For CI, run npx impeccable detect src/ to produce deterministic JSON and gate merges. The agent automatically reads PRODUCT.md and DESIGN.md each run, minimizing configuration while keeping your system authoritative.
Detects AI slop, preserves systems, and ships consistent, tasteful UI changes.
Setup and Integration
Impeccable turns diffuse AI suggestions into deliberate, auditable design changes. By naming interventions, inheriting your system, enforcing deterministic rules, and closing the loop with live previews, it upgrades agent output from good enough to commit-ready. Teams gain faster iteration without stylistic drift, safer merges, and a path to explore ambitious worlds only when a direction clearly wins.
Open the tool and review its core product experience.
Create your account or access your existing workspace.
Use your own task to judge speed, quality, and fit.
Check similar AI tools before making a final decision.
Impeccable
Impeccable is created by Paul Bakaus, focused on bridging design thinking and agentic coding workflows. The project concentrates on production-safe UI generation, precise design control, and practical tooling—commands, detectors, and live previews—that slot directly into modern developer environments and continuous integration.
Impeccable is a open-source production-grade design vocabulary and detector for agent-driven coding. Inside Cursor, Claude Code, Copilot, Gemini CLI, or Codex CLI, you issue commands like /polish, /distill, /typeset, and /audit; the sub-agent reads PRODUCT.md and DESIGN.md, edits UI code, and writes commits that respect your design system. A 58-59 rule detector blocks common AI tells (beige defaults, over-rounding, ghost cards, pulsing dots) before they ship. Live Mode attaches to a running app with an in-browser picker so you can steer page-level or element-level variants and accept results straight to source. Model-specific builds compile extra slop rules per provider and wire native hooks where supported. A Chrome extension overlays the detector on any page; a CLI provides deterministic JSON output and exit codes for CI and PR gates. Impeccable also deals reviewed "worlds" that compete with model ideas, helping teams commit to coherent graphic systems without leaving their coding environment.
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