Improve Knowledge Base Architecture.user.prompt
# Improve Knowledge Base Architecture
**Target**: `knowledge_base/` schemas and structure
**Specialty**: JSON schemas, data models, CRUD patterns, validation
**Framework**: See `knowledge_base/system_config.json` → `self_improvement_framework` for methodology, principles, and validation requirements.
---
## Knowledge Base-Specific Focus Areas
**What makes the knowledge base effective:**
1. **Schema Quality**
- Clear, extensible schemas
- Proper validation rules
- Version-control friendly
- Well-documented fields
2. **Data Organization**
- Structured JSON format
- Logical field grouping
- No redundancy
- Easy to query
3. **CRUD Patterns**
- Safe read/write operations
- Proper error handling
- Validation before writes
- Clear access documentation
4. **Integration Excellence**
- All agents use correctly
- No schema conflicts
- Smooth handoffs
- Centralized references
---
## Files in Scope
- `knowledge_base/system_config.json` - Platform config, constraints, references
- `knowledge_base/user_requirements.json` - Requirements from discovery
- `knowledge_base/design_decisions.json` - Architecture decisions
- `knowledge_base/schemas/*.schema.json` - JSON schemas for validation
---
## Integration Requirements
- References `knowledge_base/system_config.json` → `validation_framework`
- All agents read/write correctly
- Schema validation enforced
- Documentation accurate
---
## Success Criteria
Beyond standard criteria (see system_config.json), ensure:
✅ Schemas complete and extensible
✅ CRUD patterns safe
✅ All agents integrate correctly
✅ Documentation clear
✅ No redundancy
---when to use it
Community prompt sourced from the open-source GitHub repo Modular-Earth-LLC/multi-agent-ai-development-framework (MIT). A "Improve Knowledge Base Architecture.user.prompt" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
roleplaycommunitygeneral
source
Modular-Earth-LLC/multi-agent-ai-development-framework · MIT