critique
Evaluate design effectiveness across visual hierarchy, information architecture, emotional resonance, and user experience quality.
- Assesses interfaces against AI-generated design anti-patterns (color palettes, gradients, glassmorphism, generic layouts) to identify and eliminate "AI slop" tells
- Evaluates 10 core dimensions: visual hierarchy, information architecture, emotional resonance, discoverability, composition, typography, color strategy, state handling, microcopy, and affordance
- Requires frontend-design skill context and the Context Gathering Protocol; runs teach-impeccable if no design foundation exists
- Delivers structured critique reports with anti-pattern verdicts, priority issues ranked by impact, concrete fixes, and provocative questions to unlock better solutions
STEPS
Step 1: Preparation
Invoke /impeccable, which contains design principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding. If no design context exists yet, you MUST run /impeccable teach first. Additionally gather: what the interface is trying to accomplish.
Step 2: Gather Assessments
Launch two independent assessments. Neither must see the other's output to avoid bias.
You SHOULD delegate each assessment to a separate sub-agent for independence. Use your environment's agent spawning mechanism (e.g., Claude Code's Agent tool, or Codex's subagent spawning). Sub-agents should return their findings as structured text. Do NOT output findings to the user yet.
If sub-agents are not available in the current environment, complete each assessment sequentially, writing findings to internal notes before proceeding.
Tab isolation: When browser automation is available, each assessment MUST create its own new tab. Never reuse an existing tab, even if one is already open at the correct URL. This prevents the two assessments from interfering with each other's page state.
Assessment A: LLM Design Review
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