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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databank/collab/intake/templates/AI_TOOLS_TEMPLATE.md
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# AI Tools and Agent Preferences Intake Template
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## Overview
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This template guides the collection of AI tool preferences and agent interaction guidelines.
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## Interview Structure
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### 1. Current Tool Usage
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- Primary tools and their roles
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- Subscription status and limitations
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- Usage patterns and workflows
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- Strengths and limitations of each tool
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- Quota management and availability strategies
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- Backup and alternative tool selections
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### 2. Agent Guidelines and Rules
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- Core operating principles
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- Communication protocols and expectations
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- Documentation standards and formats
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- Quality assurance and validation approaches
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- Error handling and recovery procedures
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- Security and privacy considerations
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### 3. Workflow Preferences
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- Preferred interaction styles
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- Response length and detail expectations
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- Formatting and presentation preferences
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- Decision-making and approval processes
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- Feedback and iteration approaches
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- Collaboration and delegation patterns
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### 4. Technical Environment
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- Development environment preferences
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- Tool integration and interoperability
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- Version control and change management
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- Testing and quality assurance practices
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- Deployment and delivery mechanisms
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- Monitoring and observability requirements
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### 5. Performance Optimization
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- Token efficiency strategies
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- Context window management
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- Response time expectations
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- Resource utilization considerations
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- Cost optimization approaches
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- Scalability and reliability requirements
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## Response Format
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Please provide responses in the following structured format:
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```yaml
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tool_usage:
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primary_tools:
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- name: ""
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role: ""
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subscription_status: ""
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usage_patterns: []
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strengths: []
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limitations: []
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quota_management:
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strategies: []
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backup_selections: []
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workflow_integration:
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primary_flows: []
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backup_flows: []
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agent_guidelines:
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core_principles: []
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communication_protocols: []
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documentation_standards: []
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quality_assurance: []
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error_handling: []
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security_considerations: []
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workflow_preferences:
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interaction_styles: []
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response_expectations:
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length_preference: ""
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detail_level: ""
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formatting_preferences: []
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decision_processes: []
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feedback_approaches: []
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collaboration_patterns: []
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technical_environment:
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development_preferences: []
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tool_integration: []
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version_control: []
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testing_practices: []
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deployment_mechanisms: []
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monitoring_requirements: []
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performance_optimization:
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token_efficiency: []
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context_management: []
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response_time: []
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resource_utilization: []
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cost_optimization: []
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scalability_requirements: []
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```
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## Validation Criteria
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- Alignment with current tool subscriptions
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- Consistency with documented workflows
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- Practicality of implementation
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- Completeness of coverage
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- Clarity of expectations
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## Frequency
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This intake should be updated:
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- Semi-annually for tool changes
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- As-needed for workflow modifications
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- Quarterly for performance optimization reviews
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Reference in New Issue
Block a user