Intelligence Enhancement Implementation
This directory contains implementation documentation for the ModelSEEDagent Intelligence Enhancement Framework.
Directory Structure
intelligence-enhancement/
├── README.md # This file
├── phase-1-prompt-centralization.md # Phase 1 implementation guide
├── phase-2-context-enhancement.md # Phase 2 implementation guide
├── phase-3-reasoning-validation.md # Phase 3 implementation guide
├── phase-4-artifact-intelligence.md # Phase 4 implementation guide
├── phase-5-integrated-validation.md # Phase 5 implementation guide
├── research-integration.md # Research paper integration notes
├── baseline-measurements.md # Baseline intelligence metrics
└── validation-framework.md # Testing and validation approach
Overview
The Intelligence Enhancement Framework transforms ModelSEEDagent from a sophisticated tool orchestrator into a genuinely intelligent scientific analysis platform. Implementation follows a 5-phase approach over 12 days (June 18-29, 2025).
Key Goals
- Centralize Scattered Prompts: Consolidate 27+ prompts across 8 files
- Enable Transparent Reasoning: Implement traceable decision-making
- Enhance Biological Intelligence: Move from generic to mechanistic insights
- Improve Artifact Usage: Increase from 0% to 60%+ appropriate usage
- Generate Scientific Hypotheses: Enable testable hypothesis formation
Research Foundation
Based on multimodal AI reasoning research (arXiv:2505.23579v1) and GRPO composite reward approaches for balanced optimization.
Implementation Status
- Phase 0: Documentation & Baseline Assessment (June 18)
- 🔄 Phase 1: Centralized Prompt Management + Reasoning Traces (June 19-21)
- Phase 2: Dynamic Context Enhancement (June 22-23)
- Phase 3: Reasoning Quality Validation (June 24-25)
- Phase 4: Enhanced Artifact Intelligence (June 26-27)
- Phase 5: Integrated Validation (June 28-29)
Quick Start
- Review baseline assessment in
baseline-measurements.md
- Follow phase-specific implementation guides
- Use validation framework for testing improvements
- Refer to research integration for theoretical foundation
Success Metrics
Target improvements by June 29, 2025: - Artifact Usage Rate: 0% → 60%+ - Biological Insight Depth: Generic → Mechanistic - Cross-Tool Synthesis: 30% → 75% - Reasoning Transparency: Black box → Traceable - Hypothesis Generation: 0 → 2+ per analysis