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, save the result to .ai/PROMPT.md (create .ai/ directory if needed). This builds a reusable prompt library over time. Append with a heading and date:

## [Prompt Name] — YYYY-MM-DD

[refined prompt content]

Anti-Patterns