feat: implement human/LLM dual-format databank architecture with Joplin integration\n\n- Restructure databank with collab/artifacts/human/llm top-level directories\n- Move CTO and COO directories under pmo/artifacts/ as requested\n- Create dual-format architecture for human-friendly markdown and LLM-optimized structured data\n- Add Joplin integration pipeline in databank/collab/fromjoplin/\n- Create intake system with templates, responses, and workflows\n- Add sample files demonstrating human/LLM format differences\n- Link to TSYSDevStack repository in main README\n- Update PMO structure to reflect CTO/COO under artifacts/\n- Add processing scripts and workflows for automated conversion\n- Maintain clear separation between editable collab/ and readonly databank/\n- Create comprehensive README documentation for new architecture\n- Ensure all changes align with single source of truth principle
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
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# LLM-Optimized Databank
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This directory contains all databank information formatted for optimal LLM consumption. Files in this directory are:
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- Structured data in JSON, YAML, or other machine-readable formats
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- Minimally formatted for efficient parsing
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- Organized for programmatic access patterns
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- Rich with metadata and semantic structure
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- Designed for LLM token efficiency and context window optimization
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## Structure
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```
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llm/
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├── personal/ # Personal information (AboutMe.json, TSYS.yaml, etc.)
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├── agents/ # AI agent guidelines and tools (structured)
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├── context/ # General context information (structured)
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├── operations/ # Operational environment information (structured)
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├── templates/ # Template files (structured)
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├── coo/ # Chief Operating Officer information (structured)
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├── cto/ # Chief Technology Officer information (structured)
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└── README.md # This file
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```
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## Purpose
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Files in this directory are optimized for:
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- Efficient token usage in LLM context windows
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- Quick parsing and information extraction
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- Semantic search and retrieval
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- Programmatic processing and manipulation
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- Integration with AI agent workflows
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## Formats
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Files may be in various structured formats:
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- **JSON** - For hierarchical data with clear key-value relationships
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- **YAML** - For human-readable structured data with comments
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- **CSV** - For tabular data and lists
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- **XML** - For complex nested structures when needed
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- **Plain text with delimiters** - For simple, token-efficient data
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## Relationship to Human Directory
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This LLM directory is synchronized with the `../human/` directory, which contains the same information in beautifully formatted markdown for human consumption.
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---
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