Skip to main content

Agent harness and CLI to eliminate AI slop from frontend code

Project description

UIdetox

The anti-slop engine for AI-generated frontends.

UIdetox Flow

UIdetox is an agent harness that eliminates the "AI smell" from your UI. It transforms generic, LLM-generated code into hand-crafted, high-fidelity interfaces through a systematic scan → fix loop that enforces design taste and detects common AI anti-patterns.

InstallationCommandsDesign Dials


From "Vibe Coding" to "Vibe Design"

AI coding tools are great at building things fast, but the results often scream "AI made this"—Inter font, purple gradients, glassmorphism, and generic hero dashboards.

UIdetox gives your agent an objective "Design Score" to optimize. It’s not a linter; it’s a standard. By knowing what not to do, your agent can finally produce code that makes people ask "Who made this?"—not "Which AI made this?"


The Agent Prompt

Paste this into your AI coding agent (Cursor, Windsurf, Claude, etc.) to begin:

I want you to eliminate "AI slop" from this codebase and make the UI indistinguishable from hand-crafted design. Your goal is to reach a **Design Score of 95+**.

To do this, use the UIdetox ecosystem (requires Python 3.11+). Run the following setup:
pip install uidetox
uidetox update-skill [your_agent_name]  # e.g., claude, cursor, windsurf, gemini
uidetox setup --auto-commit

THE LOOP
This is a closed-loop system. Do not stop after one fix. Repeat this cycle until the strict score is maximized.
Run `uidetox loop` to bootstrap the full 5-phase protocol. The loop will guide you through:
1. Phase 0: Mechanical fixes (`uidetox check --fix`)
2. Phase 1: LLM-dynamic codebase exploration and mapping via GitNexus (`uidetox scan`)
3. Phase 2: Component-level batch fixes (`uidetox next` → fix → `uidetox batch-resolve ID1 ID2 ... --note "..."`)
4. Phase 3: Subjective review (`uidetox review` → `uidetox review --score N`)
5. Phase 4: Status check with blended Design Score (`uidetox status`)
6. Phase 5: Finalize (`uidetox finish`)

RULES OF ENGAGEMENT
1. Heavy Lifting: Don't be lazy. Large refactors and small detailed fixes — do both with equal energy. Replace entire components if they reek of AI slop. Fix things properly, not minimally.
2. Subordinate Ego: `uidetox next` injects specific SKILL.md design rules into your context. Follow them strictly. Do not substitute your own analysis or rely on your baseline training data.
3. Orchestrator: For massive codebases, the loop will prompt you to run `uidetox subagent` to spawn parallel observers. Act as a manager.

Installation

pip install uidetox

# Install the design rules for your specific environment:
uidetox update-skill claude    # (Also supports: cursor, gemini, windsurf, copilot)
uidetox setup --auto-commit    # Initializes design dials & git integration

Commands

The Engine (CLI)

Command Action
uidetox loop Enter autonomous protocol (creates session branch, guides scan → fix loop).
uidetox scan Full audit: auto-detects tooling and runs 40-rule static analyzer + dynamic prompt.
uidetox next Batches the highest-priority component issues with SKILL.md context injection.
uidetox batch-resolve Resolves a batch of issues with a single coherent commit
uidetox status View your Blended Design Score (60% static + 40% LLM review) and hints.
uidetox rescan Clears queue and re-audits with 40+ fresh anti-slop rules.
uidetox finish Squash merges the autonomous session branch cleanly.

Design Skills (Slash Commands)

Use these for targeted improvements on specific files or directories:

  • uidetox polish – Final quality and alignment pass.
  • uidetox animate – Adds purposeful motion (spring physics, scroll reveals).
  • uidetox audit – Technical checks for accessibility and performance.
  • uidetox harden – Edge cases, error handling, and i18n.

Design Dials

Control the "aesthetic DNA" of the output by adjusting these values in uidetox setup:

  • DESIGN_VARIANCE (1-10): From clean/centered (1) to asymmetric/massive whitespace (10). Drives structural layout generation patterns (Bento grids vs split-screens).
  • MOTION_INTENSITY (1-10): From CSS-only (1) to complex spring physics and reveals (10).
  • VISUAL_DENSITY (1-10): From spacious "art gallery" (1) to "cockpit mode" data density (10).

The Slop Checklist

UIdetox actively hunts and destroys:

  • Use of Emojis in text content
  • Overused Inter font stacks.
  • Generic Purple-Blue gradients.
  • Identical Card Grids with no hierarchy.
  • Meaningless Glassmorphism.
  • Default Lucide/Radix patterns with zero customization.
  • "Generic Startup" copywriting (e.g. "Next-Gen", "Elevate").
  • Div Soup over semantic HTML.
  • Missing Focus/Hover accessibility states.

Credits & License

Built on the shoulders of desloppify and impeccable

MIT © OJamals

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

uidetox-1.3.5.tar.gz (242.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

uidetox-1.3.5-py3-none-any.whl (194.1 kB view details)

Uploaded Python 3

File details

Details for the file uidetox-1.3.5.tar.gz.

File metadata

  • Download URL: uidetox-1.3.5.tar.gz
  • Upload date:
  • Size: 242.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for uidetox-1.3.5.tar.gz
Algorithm Hash digest
SHA256 0367dc05686e574d4dfe14a29b0267f8eda4d683d5d63c3743a62219011c7bca
MD5 f4b5c27342fcc753c2362fcfbc765adf
BLAKE2b-256 5010f48f909eacb08fae6419a5fcfec04ee5e5e8ea5d723bd1f4538744f44e2f

See more details on using hashes here.

File details

Details for the file uidetox-1.3.5-py3-none-any.whl.

File metadata

  • Download URL: uidetox-1.3.5-py3-none-any.whl
  • Upload date:
  • Size: 194.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for uidetox-1.3.5-py3-none-any.whl
Algorithm Hash digest
SHA256 a10e7b939ad0d94ff717de9a23d9a9ed3e2dd7688c7425410f60047f2b728d18
MD5 e6f3aaaef5d6e6f322583b25e72d1e1e
BLAKE2b-256 c459986a17cff7cd9d261a77ecf1f785c0fa947e546bc409d3269bb31c1b3164

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page