Verifiable Design Parity Constraints

We’ll demo a verifiable pipeline that translates Figma/Adobe XD designs into constraints + tokens + responsive rules, generates interactive MCP App UIs, and produces a design parity report (auditable) that proves the shipped UI honors design intent across breakpoints.

What we’re building (technical, grounded)

A design-to-agentic-UI system with four primitives:

Design ingestion (Figma/XD)

Extract design tokens (color, type scale, spacing), component semantics (buttons, cards, nav), and layout intent (grid, alignment, density).

Convert to a normalized Design Intent Spec (DIS).

Template registry (universal UI templates)

A library of parametric templates (layout archetypes + interaction patterns).

Templates accept tokens + constraints and output UI code.

Constraint manifest (the verification core)

A machine-readable manifest that encodes:

Layout constraints (grid columns, min/max widths, padding rules, alignment invariants)

Responsive rules (breakpoints, reflow behavior, truncation rules, priority ordering)

Component contracts (required states, accessibility expectations, interaction affordances)

This manifest is the “source of truth” the generator must satisfy.

MCP App UI runtime

The UI is delivered as an MCP App (interactive UI inside the client) with explicit tool bindings (UI actions → tool calls).

The same manifest drives both generation and verification.

The verification mechanism (non-brittle parity checks)

We’ll show two complementary verification layers that go beyond “apply tokens”:

A) Structural / rule-based verification (fast, deterministic)

Compile DIS → constraint assertions per breakpoint:

e.g., “card grid is 1-col under 640px, 2-col under 1024px, 3-col above”

“primary CTA remains above the fold on mobile”

“nav collapses into drawer with N max items visible”

Verify the generated UI against these assertions by analyzing:

template parameters used

layout tree structure

computed layout properties for each breakpoint (from the rendered DOM snapshot)

B) Visual / perceptual verification (tolerant, non-brittle)

Render both:

design reference (from Figma/XD export frames)

generated UI (MCP App UI at the same viewport sizes)

Compute similarity using:

a perceptual diff (SSIM/LPIPS-style) and

bounding-box alignment checks for key components (header, CTA, cards)

Output a parity score per breakpoint + annotated diffs.

The auditable output (what we’ll “pop the hood” on)

A concrete engineering artifact called a Design Parity Report, containing:

tokens applied (hashes + versions)

template IDs and parameters used

constraint manifest version

parity scores per breakpoint

annotated diffs for any violations

remediation hints (“use Template X instead of Y”, “tighten padding constraint at md breakpoint”)

This report is logged as an append-only, auditable event alongside the UI artifact, so teams can prove what changed, why it changed, and whether parity improved or regressed over time.

What we’ll demo live (5 minutes)

Start with a Figma/XD screen (desktop + mobile frames).

Ingest → generate interactive MCP App UI.

Run the parity checker across 3 breakpoints.

Show the Design Parity Report + one intentional failure (e.g., CTA drops below fold on mobile).

Fix by changing a constraint or swapping template → re-run → parity passes.