Reverse Prompting

Feed any AI output back to a model and reconstruct the prompt behind it — then improve on it. Works on images, video and text.

Most people guess at what makes a good prompt. Reverse prompting shows you. Every AI-generated thing has a prompt architecture underneath; deconstruct it and you learn faster than any tutorial teaches.

The only prompts you need to reverse-engineer, extract, and improve any AI-generated content. Feed them any image description, video scene, or output — they reconstruct the complete prompt architecture behind it, then refine and improve it to produce even better results.

WHY REVERSE PROMPTING? Most people try to guess what makes a great prompt. Reverse prompting shows you exactly. Every AI-generated image, video, or text has a hidden prompt architecture — deconstruct it, and you learn faster than any tutorial.

✦ Works on images

✦ Works on videos

✦ Works on LLM outputs

✦ Any AI model

PRO TIP: Works for any AI model — FLUX, Midjourney, Seedance 2.0, Higgsfield, ChatGPT Image 2.0, Runway, and all LLMs.

TL;DR — HOW REVERSE PROMPTING WORKS

01Copy the Universal Reverse Prompt below using the button

02Paste into GPT-4o, Claude, or Gemini as your first message

03Describe or paste the AI output you want to reverse-engineer

04Get a full 5-phase deconstruction: visual breakdown → technical params → reconstructed prompt → negative prompt → optimized version

05Use Phase 5 (Optimized Version) as your new, improved prompt

WHAT THE 5 PHASES REVEAL

PH.1Visual Breakdown — composition, lighting, color, perspective

PH.2Technical Parameters — model settings, CFG, steps, sampler

PH.3Reconstructed Prompt — the full prompt that created this output

PH.4Negative Prompt — what was excluded to achieve this quality

PH.5Optimized Version — an improved prompt that exceeds the original

★ MASTER REVERSE PROMPT — UNIVERSAL

Universal Reverse Prompt — Extracts Everything From Any AI Output

The most powerful reverse prompt ever built. Feed it any AI output — it fully deconstructs the prompt architecture, identifies every technique, extracts all hidden parameters, and improves the original prompt to produce even better results.

You are an expert AI prompt analyst and reverse engineer. Your task is to fully deconstruct any AI-generated content I provide and extract the complete prompt architecture. When I give you an AI output (image description, video scene description, or text), analyze it and provide: PHASE 1 — VISUAL/CONTENT BREAKDOWN: Identify: composition, subject positioning, lighting quality and direction, color palette, atmosphere, texture detail, perspective, focal length feel, and every significant visual element. PHASE 2 — TECHNICAL PARAMETERS: Deduce: likely AI model used, estimated CFG scale, sampling approach, resolution, aspect ratio, any LoRA or style models that may have been applied. PHASE 3 — RECONSTRUCTED PROMPT: Write the complete, optimized prompt that most likely generated this output. Include: quality tags, subject description, lighting, camera specs, mood, style references, and any technical parameters. PHASE 4 — NEGATIVE PROMPT: Write the negative prompt that was likely used to achieve this quality level. PHASE 5 — OPTIMIZED VERSION: Improve upon the original. Write an enhanced version of the prompt that would produce superior results — higher quality, more cinematic, more detailed, more intentional. Begin your analysis now. I will provide the AI output in my next message.

TEXT-TO-IMAGE REVERSE PROMPT

Image Reverse Prompt — Maximum Visual Detail Extraction

Engineered for reverse-engineering AI-generated images. Extracts every visual parameter — from pixel-level texture to macro composition choices — then rebuilds and supercharges the prompt for FLUX, Midjourney, SDXL, and Nano Banana Pro.

You are an expert visual analyst and AI image prompt engineer. Analyze the image I describe and reverse-engineer its complete prompt. For the image I provide, extract: 1. SUBJECT: exact description of who/what, clothing, expression, pose, positioning 2. LIGHTING: light source type, direction, quality, color temperature, shadows 3. CAMERA: estimated focal length, aperture (depth of field), camera height and angle 4. COMPOSITION: framing, rule of thirds, negative space, foreground/background relationship 5. COLOR GRADE: overall palette, warm/cool balance, saturation, contrast level 6. STYLE: publication or aesthetic reference (Vogue, NatGeo, editorial, documentary) 7. TECHNICAL: quality level, sharpness, grain, any post-processing artifacts Then produce: — EXACT RECONSTRUCTED PROMPT: copy-paste ready, full detail — OPTIMIZED ENHANCED PROMPT: improved version that would exceed the original quality

TEXT-TO-VIDEO REVERSE PROMPT

Video Reverse Prompt — Scene & Motion Deconstruction

Built for text-to-video AI. Deconstructs camera movement, temporal consistency, scene progression, subject motion, and cinematographic language — then reconstructs and improves the complete video prompt.

You are an expert cinematographer and AI video prompt engineer. Analyze the video scene I describe and reverse-engineer its complete prompt in Seedance 2.0 bracket format. For the scene I describe, extract: [MOTION]: what is moving, how it moves, at what pace [SUBJECT]: who/what, their consistent appearance, identity markers [ENV]: full environment description, time of day, weather, atmosphere [CAMERA]: shot type, camera movement, lens feel, frame rate [LIGHTING]: all light sources, quality, color, dramatic intent [STYLE]: director reference, cinematic language, film aesthetic [DURATION]: estimated clip length Then produce: — RECONSTRUCTED BRACKET PROMPT: complete Seedance 2.0 format — OPTIMIZED VERSION: enhanced prompt for superior temporal consistency and cinematic quality