--- name: "prompt-optimizer" description: "Paste a rough AI prompt and get an optimized version with an explanation of every improvement. Applies clarity, specificity, context-setting, output format, and constraint techniques. Works for Claude, GPT, Gemini, and any LLM." metadata: version: "1.0.0" disable-model-invocation: true --- # Prompt Optimizer > **Purpose:** Transform a rough, vague, or inconsistent AI prompt into a high-quality, optimized version. Analyzes the original for common failure modes — ambiguity, missing context, no output format spec, conflicting constraints — then produces an improved version with a diff-style explanation of every change made. Works for any LLM (Claude, GPT, Gemini, Llama). --- ## Invocation ``` /optimize-prompt ``` Paste your prompt after the command or in the next message. --- ## What Gets Analyzed ### 1. Clarity and Specificity - Is the task underspecified? ("write some code" vs "write a TypeScript function that...") - Are there ambiguous pronouns or references? - Does it state what a "good" output looks like? ### 2. Context - Is there missing background the model needs to answer well? - Should a persona or role be set? ("You are a senior security engineer...") - Is the input format specified? ### 3. Output Format - Is the expected format defined (JSON, Markdown, bullet list, numbered steps)? - Is length/verbosity specified? - Are examples of the desired output provided? ### 4. Constraints - Are there conflicting or redundant instructions? - Are hard constraints clearly marked vs soft preferences? - Is scope limited to prevent scope creep? ### 5. Chain-of-Thought - Would the model benefit from "think step by step"? - Should it show its reasoning or just the answer? --- ## Output Format ```markdown ## Original Prompt [your original prompt, quoted] --- ## Issues Found | # | Issue | Severity | Category | |---|-------|----------|----------| | 1 | [description] | High/Med/Low | Clarity/Context/Format/Constraints | --- ## Optimized Prompt [the improved prompt, ready to copy-paste] --- ## What Changed - **[Change 1]:** [explanation of why this improves the prompt] - **[Change 2]:** [explanation] --- ## Tips for This Type of Prompt [1-3 specific tips for prompts in this domain] ``` --- ## Rules - **Never change the intent** — only improve how it's expressed - **Show every change** — the explanation section must account for all edits - If the original prompt is already well-optimized (score ≥ 8/10), say so and note only minor suggestions - Rate the original prompt 1-10 for context (e.g., "Original: 4/10 — Optimized: 9/10") - If the prompt is for a specific model (Claude, GPT-4, etc.), apply model-specific best practices - Don't over-engineer simple prompts — sometimes "write a haiku about coffee" doesn't need improvement ## Playground

Input: Rough prompt

write me a function that takes
a list of numbers and removes
duplicates and also sorts it
and returns it, in python

Output: Optimized prompt

Write a Python function with this
signature:

def dedupe_sorted(nums: list[int])
  -> list[int]:

Requirements:
- Remove duplicate values
- Return elements in ascending order
- Do not modify the input list
- Handle empty list (return [])
- Type-annotated, no external imports

Example:
dedupe_sorted([3,1,2,1,3]) → [1,2,3]
dedupe_sorted([])          → []