Android gradle build
Skill adrigm06/Android-Engineering-Skill/skills/android-gradle-build
A modular, composable, production-grade Android skill system for agentic engineering workflows, designed to behave like a senior Android Staff Engineer under real-world constraints.
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Android build engineering skill for Gradle architecture, convention plugins, dependency management, and build performance. Use whenever users ask to optimize build time, modular build setup, or dependency strategy.
SKILL.md
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Purpose
Improve Android build reliability, determinism, and throughput through measurable Gradle architecture decisions and rollback-safe migrations.
Scope and authority
This skill is the lead authority for:
- build logic structure (convention plugins, build-logic topology)
- dependency and version governance
- build performance interventions and CI cache strategy
- migration sequencing for build system changes
This skill must defer when applicable:
- architecture ownership boundaries to
android-architecture - runtime performance constraints to
android-performance - production rollout gates to
android-release-engineering
When to use
- build time optimization and CI throughput issues
- multi-module Gradle structure changes
- convention plugin/build-logic migration decisions
- annotation processing strategy (KSP vs kapt) planning
- dependency governance and reproducibility hardening
Required inputs
Collect minimum evidence first:
- baseline metrics (configuration time, clean/incremental build times)
- CI topology (agents, cache behavior, matrix strategy)
- module graph shape and dependency hotspots
- plugin/version management approach
- delivery pressure and acceptable migration risk
If baseline metrics are missing, propose measurement-first phase before structural changes.
Decision engine workflow
- Baseline current build and CI behavior.
- Classify dominant bottleneck domain (configuration, task execution, dependency graph, cache reliability).
- Select intervention branch with expected impact and cost.
- Validate against architecture and release constraints.
- Define phased rollout with stop/rollback gates.
- Specify verification metrics and regression monitors.
Branching decision tree
Branch A: bottleneck classification
Configuration-heavy:- consolidate duplicated Gradle logic
- migrate reusable setup to convention plugins
Execution-heavy:- optimize hot tasks and annotation processing strategy
- reduce unnecessary task invalidation
Dependency graph-heavy:- reduce
apileakage and classpath bloat - tighten dependency exposure boundaries
- reduce
Cache instability-heavy:- fix root-cause cache misses before scaling cache infra
- enforce deterministic inputs and normalized build environments
Branch B: build logic architecture
- small module count + low duplication:
- lightweight centralization may be enough
- medium/high module count + repeated scripts:
- adopt convention plugins with explicit ownership
Branch C: annotation processing strategy
- choose
KSPwhere ecosystem support and ROI are proven - keep
kaptwhere migration risk is high or ecosystem support is incomplete - mixed mode is acceptable temporarily with migration criteria
Branch D: CI strategy
- prioritize reproducibility and deterministic cache keys before aggressive parallelization
- if release cadence is tight, gate risky build changes behind opt-in CI paths first
Quantitative gates
Use measurable gates and label each pass | at-risk | fail:
- configuration-time regression budget gate
- clean-build-time regression budget gate
- incremental-build-time regression budget gate
- cache-effectiveness gate (hit-rate and determinism trend)
If baseline build metrics are missing, run measurement-first and postpone irreversible build-graph changes.
Conflict handling and composition
When used with other skills:
- With
android-architecture:- reject build-driven module splits that violate ownership logic
- With
android-release-engineering:- release stability overrides aggressive build tuning near launch windows
- With
android-testing:- preserve test reliability while optimizing build pipeline
- With
android-performance:- avoid build optimizations that hide runtime regressions by weakening validation paths
Real-world tradeoff guidance
Accept justified non-ideal choices when explicit:
- temporary duplicated scripts may remain during phased plugin migration
- partial cache adoption is acceptable if deterministic misses are still being stabilized
- delaying deep dependency cleanup may be valid under strict deadlines if guardrails are defined
Do not represent temporary debt as steady-state architecture.
Anti-pattern detection
- repeated Gradle snippets with no central ownership
- pervasive
apidependencies increasing classpath and recompilation scope - unpinned plugin/dependency versions
- caching strategy treated as infra-only instead of input-determinism problem
- optimization proposals without baseline and post-change evidence
Uncertainty protocol
Always report confidence:
High(>= 0.80)Medium(0.60-0.79)Low(< 0.60)
For medium/low confidence:
- state assumptions and missing metrics
- provide at least one lower-risk alternative
- request the minimum additional measurements needed
- escalate to
android-release-engineeringfor near-release risk conflicts
Cross-skill handoff payload
Use the standard payload defined in ../../AGENTS.md (section: Cross-skill handoff contract).
Set requesting_skill to android-gradle-build.
Output contract
Follow global order from ../../AGENTS.md:
Context and constraintsDecision and rationaleAlternatives consideredTradeoffsRisks and mitigationsConfidence and unknownsCross-skill impactsNext implementation steps
Include build-specific artifacts:
Current build pain pointsProposed build layoutDependency/version strategyPerformance interventionsCI/cache strategyMigration plan with rollback gates
Related resources
references/build-optimization-checklist.mdreferences/quantitative-gates.md