1fdfefe631
Features: - BMAD (Build Modular AI-driven Development) framework setup - BMM, BMB, CIS, Core modules configured - Story 1.1: Component trait with error handling - Workspace Cargo.toml with components crate - 31 tests passing (19 unit + 12 doc tests) Technical: - Component trait with compute_residuals, jacobian_entries, n_equations - ComponentError enum with thiserror - JacobianBuilder for sparse matrix construction - Object-safe trait supporting Box<dyn Component> - Comprehensive documentation and examples
1.3 KiB
1.3 KiB
CSV Data File Standards
When to Use CSV
Use for:
- Domain-specific data not in training data
- Too large for prompt context
- Structured lookup/reference needs
- Cross-session consistency required
Don't use for: Web-searchable info, common syntax, general knowledge, LLM-generatable content
CSV Structure
category,name,pattern,description
"collaboration","Think Aloud Protocol","user speaks thoughts → facilitator captures","Make thinking visible during work"
Rules:
- Header row required, descriptive column names
- Consistent data types per column
- UTF-8 encoding
- All columns must be used in workflow
Common Use Cases
Method Registry
category,name,pattern
collaboration,Think Aloud,user speaks thoughts → facilitator captures
advanced,Six Thinking Hats,view problem from 6 perspectives
Knowledge Base Index
keywords,document_path,section
"nutrition,macros",data/nutrition-reference.md,## Daily Targets
Configuration Lookup
scenario,required_steps,output_sections
"2D Platformer",step-01,step-03,step-07,movement,physics,collision
Best Practices
- Keep files small (<1MB preferred)
- No unused columns
- Use efficient encoding (codes vs full descriptions)
- Document purpose
- Validate data quality