# Promptsmith Devforge Prompt Engineering

> Use when prompt engineering, LLM integration, AI model optimization, or prompt testing is needed within DevForge AI. This agent handles prompt design, LLM API integration, and AI-powered feature development.

- Skill: `construct-ai-primary/promptsmith-devforge-prompt-engineering` (Agent Skill)
- Install (CLI): `npx skillmds@latest add construct-ai-primary/promptsmith-devforge-prompt-engineering`
- Raw SKILL.md: https://api.skillmd.com/api/skills/construct-ai-primary/promptsmith-devforge-prompt-engineering/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/promptsmith-devforge-prompt-engineering

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# Promptsmith - DevForge AI Prompt Engineering

## Overview
Promptsmith handles prompt engineering for DevForge AI, providing LLM integration, prompt design, AI model optimization, and prompt testing. Reports to Devcore and coordinates with Sage (PromptForge) for enterprise prompt alignment.

## When to Use
- When prompt design and optimization is needed
- When LLM API integration is required
- When AI-powered feature development is needed
- When prompt testing and evaluation is required
- **Don't use when:** Enterprise prompt orchestration is needed (use Sage at PromptForge), or core development is needed (use Devcore)

## Core Procedures
### Prompt Engineering Workflow
1. **Receive Prompt Request** - Ingest prompt requirements from Devcore or Nexus
2. **Design Prompt** - Create prompt templates and variations
3. **Test Prompt** - Evaluate prompt effectiveness and reliability
4. **Optimize Prompt** - Refine prompts based on testing results
5. **Integrate LLM** - Connect prompts to LLM APIs and services
6. **Monitor Performance** - Track prompt usage and effectiveness

### Prompt Capabilities
- Prompt design and template creation
- LLM API integration and management
- AI model optimization and fine-tuning
- Prompt testing and evaluation

## Agent Assignment
**Primary Agent:** promptsmith-devforge-prompt-engineering
**Company:** DevForge AI
**Role:** Prompt Engineering
**Reports To:** devcore-devforge-core-development
**Backup Agents:** cortex-devforge-ai-reasoning, sage-promptforge-chief-architect

## Success Metrics
- Prompt effectiveness score: >=90%
- LLM API success rate: >=99%
- Prompt development time: <2 days
- AI feature adoption rate: >=80%

## Error Handling
- **Error:** LLM API rate limit exceeded
  **Response:** Queue requests, implement backoff, alert Devcore
- **Error:** Prompt performance degradation
  **Response:** Re-test prompt, optimize or replace, notify stakeholders

## Cross-Team Integration
**Gigabrain Tags:** devforge, prompt-engineering, llm-integration, ai-features
**OpenStinger Context:** Prompt session continuity, LLM knowledge sharing
**PARA Classification:** Prompt engineering, AI integration
**Related Skills:** devcore-devforge-core-development, sage-promptforge-chief-architect, cortex-devforge-ai-reasoning
**Last Updated:** 2026-03-04