What makes an AI prompt complex?

Complexity increases with more instructions (imperative sentences), more constraints (must/never rules), multiple role definitions, deep nesting or sub-bullets, and very high token counts. Examples decrease complexity because they clarify intent.

Is a high complexity score bad?

Not necessarily. Complex tasks need complex prompts. However, scores of 8+ often indicate the prompt could be simplified or broken into multiple calls, which usually improves model performance.

How accurate is the token count?

Token counting uses the same word-based heuristic (~1.3 tokens per word) as the AI Token Counter. Results are approximate.

AI Prompt Complexity Score

Analyze how complex your AI prompt is and understand each contributing factor.

Prompt

Paste a prompt above to score its complexity

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guide:prompt engineering basics

FAQ

What makes an AI prompt complex?: Complexity increases with more instructions (imperative sentences), more constraints (must/never rules), multiple role definitions, deep nesting or sub-bullets, and very high token counts. Examples decrease complexity because they clarify intent.
Is a high complexity score bad?: Not necessarily. Complex tasks need complex prompts. However, scores of 8+ often indicate the prompt could be simplified or broken into multiple calls, which usually improves model performance.
How accurate is the token count?: Token counting uses the same word-based heuristic (~1.3 tokens per word) as the AI Token Counter. Results are approximate.

Score your AI prompt's complexity on a 1-10 scale. Analyzes instruction count, constraint density, role mentions, nesting depth, example presence, and total token count. Shows a breakdown table so you can see which factors are making your prompt harder for the model to follow.