[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ask user whether to skip.

Quick Summary

Goal: Write and optimize prompts for AI text, image, and video generation models (Claude, GPT, Midjourney, DALL-E, Stable Diffusion, Flux, Veo).

Workflow:

1. Identify — Determine model type (LLM, image, video) and desired outcome
2. Structure — Apply model-specific prompt patterns (Role/Context/Task for LLMs, Subject/Style/Composition for images)
3. Refine — Iterate with A/B testing, style keywords, negative prompts

Key Rules:

• Use clarity, context, structure, and iteration as core principles
• Apply model-specific syntax (Midjourney --ar, SD weighted tokens, etc.)
• Load reference files for detailed guidance per domain (marketing, code, writing, data)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

AI Artist - Prompt Engineering

Craft effective prompts for AI text and image generation models.

Core Principles

1. Clarity - Be specific, avoid ambiguity
2. Context - Set scene, role, constraints upfront
3. Structure - Use consistent formatting (markdown, XML tags, delimiters)
4. Iteration - Refine based on outputs, A/B test variations

Quick Patterns

LLM Prompts (Claude/GPT/Gemini)

[Role] You are a {expert type} specializing in {domain}.
[Context] {Background information and constraints}
[Task] {Specific action to perform}
[Format] {Output structure - JSON, markdown, list, etc.}
[Examples] {1-3 few-shot examples if needed}

Image Generation (Midjourney/DALL-E/Stable Diffusion)

[Subject] {main subject with details}
[Style] {artistic style, medium, artist reference}
[Composition] {framing, angle, lighting}
[Quality] {resolution modifiers, rendering quality}
[Negative] {what to avoid - only if supported}

Example: Portrait of a cyberpunk hacker, neon lighting, cinematic composition, detailed face, 8k, artstation quality --ar 16:9 --style raw

References

Load for detailed guidance:

Topic	File	Description
LLM	references/llm-prompting.md	System prompts, few-shot, CoT, output formatting
Image	references/image-prompting.md	Style keywords, model syntax, negative prompts
Nano Banana	references/nano-banana.md	Gemini image prompting, narrative style, multi-image input
Advanced	references/advanced-techniques.md	Meta-prompting, chaining, A/B testing
Domain Index	references/domain-patterns.md	Universal pattern, links to domain files
Marketing	references/domain-marketing.md	Headlines, product copy, emails, ads
Code	references/domain-code.md	Functions, review, refactoring, debugging
Writing	references/domain-writing.md	Stories, characters, dialogue, editing
Data	references/domain-data.md	Extraction, analysis, comparison

Model-Specific Tips

Model	Key Syntax
Midjourney	--ar, --style, --chaos, --weird, --v 6.1
DALL-E 3	Natural language, no parameters, HD quality option
Stable Diffusion	Weighted tokens (word:1.2), LoRA, negative prompt
Flux	Natural prompts, style mixing, --guidance
Imagen/Veo	Descriptive text, aspect ratio, style references

Anti-Patterns

• Vague instructions ("make it better")
• Conflicting constraints
• Missing context for domain tasks
• Over-prompting with redundant details
• Ignoring model-specific strengths/limits

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IMPORTANT Task Planning Notes (MUST FOLLOW)

• Always plan and break work into many small todo tasks
• Always add a final review todo task to verify work quality and identify fixes/enhancements