research-document RFR-1FDD258C

Create a shared benchmark and decision threshold: Visual Engineering UI Anti-Patterns

RFR-1FDD258C — Create a shared benchmark and decision threshold: Visual Engineering UI Anti-Patterns

Research opportunity

Create a shared benchmark and decision threshold for the claims or recommendations in “Visual Engineering UI Anti-Patterns.”

Background

The originating artifact is accepted by the repository publishing inventory with status “active (inferred from publishable inventory).” Its Visual Engineering UI Anti-Patterns section provides the immediate evidence boundary.

Evidence trace

  • Origin document: agent-context/UI-ANTI-PATTERNS.md
  • Section: Visual Engineering UI Anti-Patterns
  • Specific assumption challenged: The source's treatment in “Visual Engineering UI Anti-Patterns” is sufficiently supported for its intended scope.
  • Supporting evidence excerpt: “- Generic containers used in place of a meaningful information model - Equal emphasis across competing elements - Color as the only state or urgency signal - Low-contrast text used to manufacture hierarchy - CSS visual reordering that conflicts with source, reading, or focus order - Responsive layouts that merely shri…”
  • Reason this opportunity exists: How competing methods or implementations compare on a common corpus with explicit utility, safety, and cost thresholds.

Unknowns

  • How competing methods or implementations compare on a common corpus with explicit utility, safety, and cost thresholds.

Dependencies

Suggested REP and methodology

  • Suggested REP: REP-VISUAL-ENGINEERING-UI-ANTI-PATTE-BENCHMARK
  • Methodology: Curate representative cases, blind ground truth where possible, define baselines and uncertainty-aware metrics, and run reproducible benchmark evaluations.
  • Expected outputs: Versioned benchmark, baseline implementations, scoring harness, datasheet, and adoption decision rule.
  • Success criteria: Independent teams can reproduce scores and the benchmark discriminates meaningful quality differences without rewarding proxy gaming.
  • Recommended agent: research-engineering-agent
  • Estimated effort: Medium
  • Expected knowledge gained: How competing methods or implementations compare on a common corpus with explicit utility, safety, and cost thresholds.

Evaluation

Dimension Score (1–5)
Knowledge gain 4
Potential impact 4
Cross-project reuse 5
Scientific importance 5
Dependency cost 5
Implementation difficulty 3
Frontier score 392

Confidence in this opportunity: moderate. Status: Open.