amr_backend_engine
CommunityMaster backend model serialization with fidelity.
Software Engineering#backend#json#camelcase#decode#structure-preservation#deserialize#model-splitting
AuthordoghelWang
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill provides a standardized workflow for decoding binary model files into CamelCase JSON, splitting them into modular fragments, and re-encoding while preserving structural fidelity and metadata.
Core Features & Use Cases
- End-to-end model lifecycle: decode .model binaries, fragment into blueprint_CompDesc.json, and re-encode with preserved type_groups and metadata.
- Safe data handling: enforces CamelCase naming, preserves metadata during deep updates via data_manager.py, and backs up CompDesc.json during initialization.
- Use Case: In AMR Studio backend workflows, ensure consistent encoding/decoding of models across components for auditability.
Quick Start
Run the decoding-splitting-encoding workflow on a target .model file to validate structural fidelity.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: amr_backend_engine Download link: https://github.com/doghelWang/amr_studio_v4/archive/main.zip#amr-backend-engine Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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