ArkUIX Module Adapter
SkillMediaGuide OHOS modules cross-platform adaptation with automated architecture analysis, code sync, and configuration generation. Use for adapting OHOS subsystem modules (@ohos.data.preferences, @ohos.intl, @ohos.multimedia.image, etc.) to Android/iOS. Provides 6-phase workflow: info collection → code sync → API analysis → architecture analysis → recommendation → implementation. Includes automated scripts for DTS analysis, architecture analysis, and configuration generation.
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Then ask your AI: use the ArkUIX Module Adapter skill
What this skill tells your AI
The instructions your AI receives, as published by openharmonyinsight/openharmony-skills in skills/arkuix-module-adapter/SKILL.md and read by ahel’s review.
Overview
Guide OHOS modules through cross-platform adaptation with automated analysis and code generation. This skill transforms Claude into a specialized adaptation assistant with domain expertise in OHOS/ArkUI-X architecture.
Quick Start
User: "I need to adapt @ohos.data.preferences module"
The skill automatically guides through all 6 phases of adaptation.
6-Phase Workflow
Phase 1: Information Collection
Collects minimal information upfront (module name), then lazily collects additional details (repository name, storage path) only when needed.
Output: Module identification information
Phase 2: Code Existence Check & Sync
Intelligently checks if OHOS code already exists before syncing. Avoids redundant operations.
Decision Tree:
- Check
.repo/manifests/openharmony-master.xml - Check
plugins/directory - Only sync if both checks fail (with repository verification on GitCode)
Output: Sync status or repository verification results
Phase 3: API Interface Analysis
Analyzes .d.ts file to determine @crossplatform coverage.
Metrics:
- Total interface count (by category)
- Adapted vs needs adaptation counts
- Coverage percentage
- Detailed list of interfaces needing adaptation
Output: Comprehensive API statistics with coverage progress bar
Automation: scripts/dts_analyzer.py interface/sdk-js/api/@ohos.{module}.d.ts
Phase 4: Architecture Analysis
Analyzes OHOS module code composition and platform dependencies.
Analysis Dimensions:
- Code volume statistics (NAPI, business logic, platform-specific)
- Platform dependency ratio
- Internal and external dependencies
- Platform implementation necessity (C/C++ native vs platform-specific code)
- Architecture diagrams (module structure, dependencies, call flow)
Key Rule: C/C++ Cross-Platform Native Support
- Analyzes whether module actually requires Android/iOS platform code
- Many data modules (preferences, RDB, crypto) are pure C/C++ and require zero platform-specific implementation
- Only path/configuration differences needed (~50 lines per platform)
Output: Detailed code composition and dependency analysis
Automation: scripts/architecture_analyzer.py foundation/{module_path}
Phase 5: Architecture Recommendation
Recommends adaptation mode based on analysis: OHOS Reuse / Independent / Hybrid
Decision Matrix:
| Mode | Code Reuse | New Code | Time | Best For |
|---|---|---|---|---|
| OHOS Reuse | 90-95% | 500-800 lines | 4-6 weeks | Data-focused (preferences, kv_store) |
| Hybrid | 60-80% | 1,500-2,500 lines | 6-10 weeks | Mixed (location, sensor) |
| Independent | 10-30% | 4,000-6,000 lines | 10-16 weeks | Platform-heavy (BLE, pasteboard) |
Output: Recommended mode with rationale and effort estimates
Phase 6: Implementation Guidance
Provides actual implementation code with complete examples for:
- Pure virtual interface (OHOS repo)
- OHOS thin wrapper (100% forwarding)
- Android JNI adapter (complete with error handling)
- iOS Objective-C++ adapter (complete with @try-@catch)
- Build configuration (GN templates)
- Unit tests
Output: Production-ready code with comprehensive error handling
Automation: scripts/code_generator.py {module} {repo} --api-version {ver}
Key Features
🤖 Automated Scripts
All scripts are in scripts/ directory:
# Analyze .d.ts coverage
python3 scripts/dts_analyzer.py interface/sdk-js/api/@ohos.data.preferences.d.ts
# Analyze module architecture
python3 scripts/architecture_analyzer.py foundation/distributeddatamgr/preferences
# Generate configuration files (dry-run)
python3 scripts/code_generator.py data/preferences distributeddatamgr_preferences --api-version 23 --dry-run
# Apply changes
python3 scripts/code_generator.py data/preferences distributeddatamgr_preferences --api-version 23
📚 Progressive Disclosure
Core workflow in SKILL.md (this file), detailed content in references:
- Phase Details:
references/phase{1-6}*.md - Architecture Modes:
references/architecture-modes.md - Code Examples:
references/code-examples.md - Templates:
assets/templates/(code templates for reuse)
🎯 Three Architecture Modes
OHOS Reuse Mode (90-95% reuse)
For data-focused modules with minimal platform dependencies.
Characteristics:
- Platform-independent business logic >90%
- Thin platform adapters (JNI/ObjC++)
- Zero OHOS runtime overhead
- C/C++ Native modules may require zero platform code (up to 100% reuse)
Example Modules: preferences, kv_store, http
Independent Implementation Mode (10-30% reuse)
For modules with heavy platform API dependencies.
Characteristics:
- Platform-specific code >70%
- Native framework integration
- Each platform has own implementation
Example Modules: bluetooth, pasteboard, camera
Hybrid Mode (60-80% reuse)
For mixed data/platform logic modules.
Characteristics:
- Extract common data structures
- Service abstraction layer
- Shared business logic
Example Modules: geolocation, sensor, request
Implementation Checklist
Use this checklist to track adaptation progress:
Phase 1: Information Collection
- Module name collected
- Repository name verified (if needed)
Phase 2: Code Sync
- Repository verified on GitCode
- Code synced (if needed)
- Plugin structure created (if needed)
Phase 3: API Analysis
- .d.ts file analyzed
- Coverage percentage calculated
- Interfaces needing adaptation listed
Phase 4: Architecture Analysis
- Code volume statistics collected
- Platform dependency ratio calculated
- Dependencies identified
- Platform implementation necessity analyzed (C/C++ native vs platform-specific)
Phase 5: Architecture Recommendation
- Architecture mode selected
- Developer confirms choice
Phase 6: Implementation
- Pure virtual interface defined (OHOS repo)
- OHOS thin wrapper implemented (OHOS repo)
- Android adapter implemented (Plugin repo)
- iOS adapter implemented (Plugin repo)
- Build configuration updated
- Configuration files generated (4 files)
- Unit tests written
- Compilation successful (all platforms)
- Tests passing
Mandatory Configuration Files
After code generation, ensure all 4 files are updated:
-
plugins/plugin_lib.gni- Module entry -
interface/sdk/plugins/api/apiConfig.json- Library configuration -
build_plugins/sdk/arkui_cross_sdk_description_std.json- Build entries -
interface/sdk-js/api/@ohos.{module}.d.ts- @crossplatform annotations
Troubleshooting
Repository not found on GitCode?
- Browse https://gitcode.com/org/openharmony/repos manually
- Try naming pattern:
{subsystem}_{module}or{module}
Validation failed?
- Check all 4 mandatory files exist
- Verify module name format (use forward slashes)
- Ensure .d.ts file path is correct
Build errors?
- Check GN configuration syntax
- Verify dependency declarations
- Check for missing includes
Related Skills
- arkuix-api-adapter - For adapting individual API methods within a module
Tips
- Start Small: Try with a simple module first (e.g., preferences)
- Use Dry-Run: Always use
--dry-runflag before applying changes - Verify Repository: Always verify repository exists before syncing
- Read References: Consult detailed references for complex phases
- Run Tests: Always run tests after implementation
Signals
- GitHub stars
- 34
- Forks
- 7
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
arkuix-module-adapter- Source
- github.com/openharmonyinsight/openharmony-skills