Constraint Specification

Constraints are the rules that shape AI output — what format to use, how long to be, what to include, what to exclude. Well-specified constraints produce predictable, useful outputs. Vague constraints produce inconsistent results.

Types of Constraints

Format constraints:

• Output structure (JSON, markdown, plain text, bullet points, prose)
• Section headings and organisation
• Required fields and optional fields
• Data types and schemas Length constraints:
• Word count ranges (not exact numbers — models are bad at counting)
• Section length proportions ("spend 60% on analysis, 40% on recommendations")
• Minimum and maximum bounds
• Conciseness directives ("be brief" vs. "be thorough") Content constraints:
• Topics to include and exclude
• Required information elements
• Prohibited content
• Source restrictions (only use provided context, don't use external knowledge) Tone constraints:
• Formality level