Refining Prompts

Process

1. Assess -- Identify what the prompt is missing:

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 vague actions ("analyze", "process", "handle") with measurable ones ("list the top 3", "classify as A/B/C", "return JSON with keys X, Y").
• One output format -- specify exactly one format (JSON schema, markdown template, numbered list). Ambiguous format expectations cause inconsistent results.
• No meta-commentary -- output only the refined prompt as markdown. No preamble ("Here's an improved version..."), no explanation of changes unless explicitly requested.

Persistence

After refining, offer to save the result to .ai/PROMPT.md -- do not write without user confirmation. If approved, append with a heading and date:

## [Prompt Name] -- YYYY-MM-DD

[refined prompt content]

Anti-Patterns

Constraints

• Stop refining if the original intent is unclear -- clarify first
• Do not refine prompts for harmful or illegal tasks

Verify

• Rewrite addresses every gap identified in the assessment
• Length ratio within 0.75x-1.5x of original (unless structural change justified)
• No invented constraints or assumptions not in the original