prompt-enricher

To add constraints and edge cases to an AI prompt, use a prompt enrichment process that extracts architectural limits, lists ambiguities, and defines scope boundaries. This transforms raw prompts into constraint-aware briefs to prevent scope drift.

Prompt enrichment is the process of grounding raw prompts with discovered constraints, ambiguities, and edge cases. You need it in software engineering workflows after gathering project context and before exploring ideas to ensure realistic AI outputs.

You generate a constraint-aware brief by applying an enrichment process to existing project context. This detects architectural and data constraints, auto-generates likely edge cases, and saves the results in an enriched-prompt.md file.

No, prompt enrichment requires an existing context.md file to function properly. It applies after context gathering to derive constraints and ambiguities from the established project environment, ensuring reliable outputs.

The best way to resolve ambiguities in raw prompts is to use an enrichment step that lists decisions needing clarification. This reduces back-and-forth communication by explicitly framing in-scope versus out-of-scope boundaries before idea exploration.