Jetpack Compose Audit

This skill audits Android Jetpack Compose repositories with a strict, evidence-based report.

Rubric version: v1 — current as of 2026-04-13. Compose track: Kotlin 2.0.20+ / Compose Compiler 1.5.4+ (Strong Skipping Mode default).

It is intentionally focused on four categories:

• Performance
• State management
• Side effects
• Composable API quality

This skill does not score design or Material 3 compliance in v1. If the audit surfaces likely design-system problems, recommend a follow-up audit with the material-3 skill (reference implementation: https://github.com/hamen/material-3-skill).

Out Of Scope In v1

Owned and deliberate scope choices — call out the limitation in the report rather than silently producing thin coverage:

• Material 3 compliance, theming, color/typography tokens — defer to the material-3 skill.
• Accessibility scoring (semantics, content descriptions, touch-target sizing) — flag obvious gaps as a note, do not score.
• UI test coverage and Compose test rule patterns — note presence/absence, do not score.
• Compose Multiplatform-specific rules (expect/actual, target-specific code paths).
• Wear OS / TV / Auto / Glance surfaces.
• Build performance (incremental compilation, KSP/KAPT choice).

If the user explicitly asks for any of these, narrow the scope and state it in the report.

When To Use

Use this skill when the user asks to:

• audit a Jetpack Compose repository
• review Compose architecture or quality
• rate a codebase with scores
• inspect recomposition, state, or effects issues
• identify Compose best-practice violations in an existing repo

Typical trigger phrases:

• "audit this Compose repo"
• "score this Jetpack Compose codebase"
• "review state hoisting and side effects"
• "check Compose performance"
• "rate this repository"

Expected Output

Produce both:

• a repository report file named COMPOSE-AUDIT-REPORT.md
• a short chat summary with the overall score, category scores, worst issues, and the top fixes

Audit Principles

• Be strict, but evidence-based.
• Do not score from search hits alone. Read representative files before judging a category.
• Cite concrete file paths in the report for every important deduction.
• Cite an official documentation URL for every deduction. No "trust me" findings — the rubric maps every rule to a canonical source in references/canonical-sources.md. The report template requires a References: line per finding.
• Prefer canonical Android guidance over folklore.
• Treat performance as important, but not as the only lens.
• Do not punish app code for failing public-library purity tests. Apply API-quality checks mainly to reusable internal components, design-system pieces, and shared UI building blocks.
• Reserve 0-3 scores for repeated or systemic problems, not isolated mistakes.
• Do not award 9-10 unless the repo is consistently strong across the category.

Process

1. Confirm Scope

Identify the target path:

• If the user passed an explicit path ([repo path or module path]), use it.
• If no path was passed, default to the current working directory.
• If the path does not exist, ask the user to clarify.

Before mapping modules, confirm Compose is actually present (fast-fail):

• grep for androidx.compose in any build.gradle* or libs.versions.toml
• grep for setContent { or @Composable under src/

If neither shows up, stop and report that the target is out of scope. Do not run a full module map first.

If Compose is present only in samples/, demos/, or test sources (no production usage), narrow the scope to those directories, set confidence to Low, and state in the report that the audit is over sample code rather than production paths. Do not score production-quality categories against demo code.

2. Map The Repository

Before scoring, identify:

• Gradle modules
• Android app and feature modules
• likely Compose source roots
• shared UI/component packages
• theme or design-system packages
• state holder or ViewModel areas
• test and preview locations
• baseline-profile related modules or config if present

3. Build A Compose Surface Map

Look for:

• @Composable functions
• reusable UI components
• screens and routes
• ViewModel usage
• remember, rememberSaveable, mutableStateOf
• collectAsStateWithLifecycle, collectAsState
• LaunchedEffect, DisposableEffect, SideEffect, rememberUpdatedState, produceState
• LazyColumn, LazyRow, items, itemsIndexed

If the repo is large, audit by category or by module. If subagents are available, parallelize category scans by spawning Explore-type subagents (no write tools) and merge the findings.

4. Generate Compose Compiler Reports (Automatic)

Do not ask the user to edit build.gradle or run commands themselves. The skill runs the build with a bundled Gradle init script that injects reportsDestination / metricsDestination into every Compose module without modifying any file in the target repo. Before scoring, attempt this:

1. Locate the init script shipped with the skill: scripts/compose-reports.init.gradle. The absolute path is the skill's install location — in most installs that's ~/.claude/skills/jetpack-compose-audit/scripts/compose-reports.init.gradle. If you cannot resolve the path, fall back to writing the script to <target>/.compose-audit-reports.init.gradle and delete it after the run.

2. Check for a Gradle wrapper in the target: test -x <target>/gradlew. If missing, skip to the fallback in step 6.

3. Pick a compile target. Prefer the cheapest task that still triggers Kotlin compilation for a Compose module:

   • find the first application module via rg -l 'com\.android\.application' -g '*.gradle*'
   • try in order: :<app-module>:compileReleaseKotlinAndroid, :<app-module>:compileReleaseKotlin, assembleRelease, assembleDebug
   • If the project is Compose-only on a library (com.android.library), use that module instead.

4. Run the build. Inform the user the build is starting (it may take several minutes).

   cd <target> && ./gradlew <task> \
       --init-script <path-to>/compose-reports.init.gradle \
       --no-daemon --quiet

   Use a 600-second timeout. If the task fails, try the next fallback task in step 3 once. Do not loop indefinitely.

5. Collect the reports.

   find <target> -path '*/build/compose_audit/*' \
       \( -name '*-classes.txt' -o -name '*-composables.txt' -o -name '*-composables.csv' -o -name '*-module.json' \)

   From these files, extract:

   • unstable classes (lines starting with unstable class in *-classes.txt) used as composable parameters
   • non-skippable but restartable named composables (ignore zero-argument lambdas; focus on actual named functions in *-composables.txt or *-composables.csv where isLambda == "0")
   • module-wide skippability counts from *-module.json, AND compute the named-only skippability from *-composables.csv (by filtering out rows where isLambda == "1" and calculating sum(skippable) / sum(restartable)). Cite both in the Performance section, noting that zero-argument lambdas can artificially anchor the module-wide metric.

6. Fallback if the build fails or Gradle is unavailable. Proceed with source-inferred stability findings, but:

   • set Compiler diagnostics used: no in the report's Notes And Limits and explain the failure reason briefly (wrapper missing, compile error, timeout)
   • reduce overall confidence by one level
   • state each stability-related deduction as "inferred from source — not verified against compiler reports"

Stability deductions from step 5 are measured evidence and should be weighted normally. Fallback deductions from step 6 are inferred and must be flagged as such in the report.

5. Audit The Four Categories

Use the scoring rubric in references/scoring.md and the heuristics in references/search-playbook.md.

Performance

Focus on:

• expensive work in composition
• avoidable recomposition
• lazy list keys
• bad state-read timing
• unstable or overly broad reads
• backwards writes
• obvious release-performance hygiene where visible

State Management

Focus on:

• hoisting correctness
• single source of truth
• reusable stateless seams
• correct use of remember vs rememberSaveable
• lifecycle-aware observable collection
• observable vs non-observable mutable state

Side Effects

Focus on:

• side effects incorrectly done in composition
• correct effect API choice
• effect keys
• stale lambda capture
• cleanup correctness
• lifecycle-aware effect behavior

Composable API Quality

Focus on reusable internal components, not every leaf screen.

Check:

• modifier presence and placement
• parameter order
• explicit over implicit configuration
• meaningful defaults
• avoiding MutableState<T> or State<T> parameters in reusable APIs where a better shape exists
• component purpose and layering

6. Verify Findings

Before deducting points:

• read the file where the smell appears
• make sure the pattern is real, not a false positive
• check whether the repo already has a compensating pattern elsewhere
• distinguish one-off mistakes from systemic patterns
• for stability findings (skippable / restartable / unstable params), use the compiler reports generated in Step 4. Cite the specific report line (e.g. app/build/compose_audit/app_release-classes.txt:42) as evidence. Only fall back to source-inferred stability claims if Step 4 failed, and label them as such.

7. Score

Assign each category a 0-10 score and a status:

• 0-3: fail
• 4-6: needs work
• 7-8: solid
• 9-10: excellent

Use the weights in references/scoring.md to compute the overall score.

Measured ceilings are mandatory, not suggestive. When Step 4 produced compiler reports, the Performance rubric in references/scoring.md defines a ceiling based on skippable% and unstable-param count. After arriving at a qualitative Performance score, you MUST apply the ceiling and lower the score if it exceeds the cap. Show the math in the report:

Performance ceiling check:
  skippable% = 186/273 = 68.1% → falls in 50-70% band → cap at 4
  qualitative score: 7
  applied score: 4 (ceiling lowered from 7)

Do not round skippable% up into a higher band. 68.1% is not ≥70%. If a qualitative score lands at or below the ceiling, no adjustment is needed — but the check itself must appear in the report so the reader can audit it.

If a category genuinely has too little auditable surface area, mark it N/A, explain why, and renormalize the remaining weights.

8. Write The Report

Use references/report-template.md.

The report must include:

• overall score
• category score table
• top critical findings
• category-by-category reasoning
• evidence file paths
• prioritized remediation list
• optional follow-up note to run material-3 if design issues are suspected

Write the report to:

• COMPOSE-AUDIT-REPORT.md inside the audited target (the path the user passed), not the current working directory.

If COMPOSE-AUDIT-REPORT.md already exists at that path, do not overwrite it silently. Either confirm overwrite with the user, or write to COMPOSE-AUDIT-REPORT-<YYYY-MM-DD>.md alongside it.

9. Return A Short Summary

In chat, produce a summary that mirrors the report's Prioritized Fixes section — not a generic recap. The developer should be able to act on the summary alone without opening the report file.

Include:

• overall score (and the delta vs. any prior COMPOSE-AUDIT-REPORT*.md at the same path, if present)
• one-line judgment for each category, with the applied ceiling if any (e.g. "Performance 6/10 — capped by 79% skippability")
• compiler-report highlights when Step 4 succeeded: Strong Skipping on/off, skippable%, count of unstable shared types, any module that failed to build
• top three actionable fixes, each with:
  • the concrete change ("add key = { it.id } to items(...) in feed/FeedList.kt:42")
  • file path(s) and line numbers — the same ones listed in the report's Prioritized Fixes
  • one official doc URL from references/canonical-sources.md
  • expected impact ("unlocks skipping for FeedItem, should move skippable% from 79% → ~90%")
• whether a material-3 audit is worth running next

The top-three fixes in the chat summary MUST be the same items as the report's Prioritized Fixes list (same file paths, same doc links). Do not add generic advice in chat that isn't in the written report.

Evidence Rules

• Prefer multiple examples over one dramatic example.
• Use positive evidence too, not just failures.
• Do not infer runtime problems you cannot justify from the code.
• When a rule is based on official guidance but app-level tradeoffs may justify deviation, call it out as a tradeoff instead of pretending it is always wrong.

Large Repo Strategy

For medium or large repositories:

1. Map modules first.
2. Pick representative files per module.
3. Parallelize category scans when possible.
4. Merge repeated findings into systemic issues instead of listing the same smell twenty times.

What To Avoid

• Do not produce a generic checklist with no repository evidence.
• Do not turn the report into a public-library API lecture if the repo is an app.
• Do not inflate the performance score just because the app uses Compose.
• Do not over-penalize isolated experiments or sample files unless they are part of production paths.
• Do not score design in v1.
• Do not flag LaunchedEffect(Unit) or LaunchedEffect(true) on its own — the "run once" pattern is idiomatic. Only flag it when the body captures a value that may change without rememberUpdatedState.
• Do not deduct on Compose Multiplatform code paths for Android-only APIs (collectAsStateWithLifecycle, lifecycle-runtime-compose). Note the platform constraint as a tradeoff instead.
• Do not double-count the same root cause across categories. A stability problem typically surfaces in both Performance and State — pick the dominant category and cross-reference.

References

• references/scoring.md — per-rule rubric with inline citations
• references/search-playbook.md — search patterns and red-flag heuristics
• references/report-template.md — required structure for COMPOSE-AUDIT-REPORT.md
• references/canonical-sources.md — the official URLs every deduction must cite
• references/diagnostics.md — copy-pasteable Gradle/code snippets for Compose Compiler reports, stability config, baseline profiles, and R8 checks
• scripts/compose-reports.init.gradle — Gradle init script the skill injects via --init-script in Step 4 to generate compiler reports automatically