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Sub-skill of modular-architecture-documentation: Overview (+6).
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | modular-architecture-documentation-overview |
| description | Sub-skill of modular-architecture-documentation: Overview (+6). |
| version | 1.0.0 |
| category | business |
| type | reference |
| scripts_exempt | true |
Following DEC-003 (Modular Architecture Decision, 2025-07-27), the system is organized into three independent modules to support gradual feature adoption and independent development cycles.
Module 1: Invoice Automation
aceengineer_admin.invoice:maininvoice-genModule 2: Tax Preparation
See sub-skills for full details.
Each module:
Phase 1: Invoice Automation (Weeks 1-2)
Phase 2: Tax Preparation (Weeks 3-4)
Phase 3: Tax Filing (Weeks 5-8)
Users can adopt modules in any order based on business priorities.
# Module 1: Invoice Automation
invoice-gen --client mkt-a --month 2025-01 --template monthly
invoice-gen --all-clients --month 2025-01 --email
# Module 2: Tax Preparation
tax-prep --year 2024 --type federal
tax-prep --year 2024 --expense-report --validate
# Module 3: Tax Filing
tax-file --year 2024 --form 1120
tax-file --year 2024 --form k1 --shareholder all
src/aceengineer_admin/
├── invoice/ # Module 1: Invoice Automation
│ ├── __init__.py
│ ├── __main__.py # CLI entry point
│ ├── generator.py # Invoice generation logic
│ ├── templates.py # Template processing
│ └── config.py # Invoice config
├── tax_prep/ # Module 2: Tax Preparation
│ ├── __init__.py
*See sub-skills for full details.*
## Testing Strategy
- **Unit Tests:** 80% coverage minimum per module, 95% for critical modules
- **Integration Tests:** Cross-module workflows (tax prep → tax filing)
- **CLI Tests:** Command-line interface validation
- **Independence Tests:** Each module testable in isolation with mocks
decisions.md:
Class-level Gmail and email operations: multi-account setup, OAuth, triage, extraction, archiving, attachments, unsubscribe, and touchbase workflows.
Conventions for creating consistent Mermaid diagrams including decision node layout, edge ordering, and flowchart direction rules.
Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.
Class-level Hermes local configuration and setup workflows, including config audit gotchas and Windows installation.
Guide AI model selection based on task complexity, cost constraints, and latency requirements
Sub-skill of modular-architecture-documentation: 1. Module Definition Framework (+9).