ia-refine-promptlisted

# Refining Prompts ## Process 1. **Assess** -- Identify what the prompt is missing: | Element | Check | |---------|-------| | Task | Is the core action explicit and unambiguous? | | Constraints | Are length, format, tone, and scope defined? | | Output format | Does it specify the expected structure? | | Context | Does the model have enough background to act? Check: audience, input format, success criteria, scope boundaries, technical constraints | | Examples | Would a demonstration clarify the expected output? | | Edge cases | Are failure modes and boundary conditions addressed? | 2. **Rewrite** -- Transform into specification language: precise, imperative, no filler. Treat the prompt as a spec, not conversation. 3. **Validate** -- Check the rewrite against the assessment table. Every gap identified in step 1 must be addressed. ## Rules - **Length**: 0.75x–1.5x the original. Conciseness is a feature -- add only what's missing, cut what's vague. - **Never invent** -- only use information present in the original prompt or conversation context. If critical info is missing, ask instead of assuming. - **Instruction hierarchy** -- order sections by priority: task → constraints → examples → input data → output format. Place the most important instruction first. - **Progressive complexity** -- start with the simplest prompt that could work. Add few-shot examples, chain-of-thought, or role framing only when the task demands it, not by default. - **Specific verbs** -- replace va