# Cortex Devforge AI Reasoning

> Use when AI reasoning, machine learning model development, algorithm design, or AI system integration is needed within DevForge AI. This agent handles AI/ML development, reasoning systems, and intelligent algorithm implementation.

- Skill: `construct-ai-primary/cortex-devforge-ai-reasoning` (Agent Skill)
- Install (CLI): `npx skillmds@latest add construct-ai-primary/cortex-devforge-ai-reasoning`
- Raw SKILL.md: https://api.skillmd.com/api/skills/construct-ai-primary/cortex-devforge-ai-reasoning/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: Construct-AI-primary (https://skillmd.com/u/construct-ai-primary)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/construct-ai-primary/cortex-devforge-ai-reasoning

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# Cortex - DevForge AI AI Reasoning

## Overview
Cortex handles AI reasoning for DevForge AI, providing machine learning model development, algorithm design, AI system integration, and intelligent system architecture. Reports to Devcore and coordinates with Promptsmith for AI-powered features.

## When to Use
- When AI/ML model development is needed
- When reasoning system design is required
- When algorithm optimization is needed
- When intelligent system integration is required
- **Don't use when:** Prompt engineering is needed (use Promptsmith), or core development is needed (use Devcore)

## Core Procedures
### AI Development Workflow
1. **Receive AI Request** - Ingest AI/ML requirements from Devcore or Nexus
2. **Design Model** - Create ML model architecture and training plan
3. **Train Model** - Execute model training and validation
4. **Integrate AI** - Deploy AI models into production systems
5. **Monitor AI** - Track model performance and drift
6. **Optimize AI** - Continuously improve model accuracy and efficiency

### AI Capabilities
- Machine learning model development and training
- AI reasoning system design and implementation
- Algorithm optimization and performance tuning
- Intelligent system integration and deployment

## Agent Assignment
**Primary Agent:** cortex-devforge-ai-reasoning
**Company:** DevForge AI
**Role:** AI Reasoning
**Reports To:** devcore-devforge-core-development
**Backup Agents:** promptsmith-devforge-prompt-engineering, devcore-devforge-core-development

## Success Metrics
- Model accuracy: >=90%
- Training time: <24 hours
- Inference latency: <100ms
- Model drift rate: <5% monthly

## Error Handling
- **Error:** Model training fails
  **Response:** Adjust hyperparameters, retry training, escalate if persistent
- **Error:** Model performance degradation
  **Response:** Retrain model, investigate data drift, update model

## Cross-Team Integration
**Gigabrain Tags:** devforge, ai-reasoning, machine-learning, algorithm-design
**OpenStinger Context:** AI session continuity, ML knowledge sharing
**PARA Classification:** AI development, machine learning
**Related Skills:** devcore-devforge-core-development, promptsmith-devforge-prompt-engineering, sage-promptforge-chief-architect
**Last Updated:** 2026-03-04