Android
AuraScore 81/100

Jetpack Compose Performance Diagnostic and Triage Matrix

Profile and prioritize Jetpack Compose UI rendering bottlenecks into a remediation matrix.

Use this template when auditing client Android applications suffering from UI jank, excessive recompositions, or slow frame rates in Jetpack Compose. It produces a detailed triage matrix mapping recomposition root causes to corrective patterns.

Template

Role: Lead Android Performance Engineer specializing in Jetpack Compose and rendering diagnostics.

Context

  • Client Portal App: {{client_portal_app}}
  • Jetpack Compose / Kotlin Version: {{compose_compiler_version}}
  • Profiler Trace Metrics: {{profiling_trace_data}}
  • Target Hardware Tiers: {{target_device_tiers}}
  • Critical User Journeys: {{critical_user_journeys}}
  • State Management Pattern: {{state_management_pattern}}

Task

Produce an actionable Jetpack Compose performance diagnostic matrix that pinpoints rendering bottlenecks, unstable composable arguments, and memory churn across critical application journeys.

Method

  1. Correlate frame drops and micro-jank events from {{profiling_trace_data}} with the UI flows in {{critical_user_journeys}}.
  2. Analyze composable compiler metrics outputs to detect unstable parameter classes, lambdas, and collection instances.
  3. Evaluate state read scopes and deferment opportunities (e.g., derivedStateOf, Modifier.offset lambda).
  4. Assess layout measurement overhead and unconstrained subcomposition costs in LazyLists and BoxWithConstraints.
  5. Inspect image loading, bitmap decoding pipelines, and vector drawing overhead across {{target_device_tiers}}.
  6. Investigate state hoppers and recomposition propagation risks stemming from {{state_management_pattern}}.
  7. Quantify memory allocation rates to identify garbage collection pressure during rapid scroll animations.
  8. Synthesize issues into a prioritized triage matrix ranked by frame budget impact and resolution effort.

Constraints

  • MUST categorize recomposition root causes using official Compose stability classifications (Stable, Immutable, Unstable).
  • MUST NOT recommend global migration back to Android Views as a performance workaround.
  • All remediation items must include exact code-level anti-patterns and their target refactored state.
  • Target frame delivery MUST respect the 16ms (60fps) and 8ms (120fps) rendering budgets.

Output format

  • Diagnostic Executive Summary (150 words)
  • Compose Performance Triage Matrix: Markdown table with columns: [Screen / Composable, Issue Pattern, Stability Classification, Frame Drop Severity (Low/Med/High/Critical), Root Cause Analysis, Recommended Refactor, Verification Method]
  • Stability & State Best Practices (bulleted technical guidance)
  • Continuous Profiling CI Integration Plan (ordered steps)

Self-review

  • Ensure each entry in the matrix cites specific Composable names and stability metrics.
  • Validate that proposed solutions directly fix unstable parameter types or deferred state reads.
  • Verify compatibility of recommendations with {{compose_compiler_version}}.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

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