refine-prompt

# 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? | | Reader | Will a model parse this with no human available to disambiguate? If yes, apply Machine-Parsed Text below. | 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. - **A line must change behavior.** "Cut what's vague" and "cut what the model already does" are different filters, and the second removes far more -- every line reads as non-vague once it is imperative. If the model would act that way by default, delete the whole sentence rather than trimming words from it. The recurring offender is encouragement it already follows: "be careful", "be thorough", "think it through...