White-Background Product Shot

White-Background Product Shot

A phone snapshot held in your hand becomes a marketplace hero image. The most-used prompt among small sellers.

Use for marketplace listings, secondhand sale posts

Tools Nano Banana Pro

Prompt

Identify the main product in the uploaded photo (automatically removing any hands holding it or messy background details). Recreate it as a premium e-commerce product shot. Subject isolation: cleanly extract the product, completely removing any fingers, hands, or clutter. Background: pure white studio background (RGB 255,255,255) with a subtle, natural contact shadow at the base. Lighting: soft commercial studio lighting to highlight texture and material, even illumination, no harsh glare. Retouching: fix lens distortion, improve sharpness, and color-correct so the product looks brand new.

Tips

Change 'pure white' to 'light wood table' for a lifestyle shot.
Add 'keep label text exactly' if labels change.

Sources

ZeroLu/awesome-nanobanana-pro §4.2 (GitHub)

License: MIT (ZeroLu/awesome-nanobanana-pro).

Prompt Dexbuilderlog.net · PROMPT DEX · FALL 2026 · 46 PROMPTS

We hunt the AI prompts people brag about on X, Instagram, TikTok, YouTube, Reddit and GitHub, and file them by what you want to make. Only prompts with public results or ones we ran ourselves, each with a rating and token estimate. This English edition carries the most-copied entries; the Korean dex has all 400+.

📦 Automation packs 🆓 Free prompts

000prompts

0.0avg rating / 5

0reproduced · tested locally

0need your photo

caught0/ 0

LAST SYNC

🆓 Free prompts, hand-picked

Copy and use right away

Browse the full dex ↓

🐙 GitHub open source

🎯 What do you want to make?

Pick a goal to see a skill tree of prompts, branch by branch

Dex

📡 Live inbox

Scraped daily from GitHub, prompt collections and Hacker News. Unverified until a human reviews it

collecting▮

★ Ratings

5: almost never fails, usable as-is
4: one or two regenerations
3: fun but inconsistent or weakly grounded

🔋 Tokens

Input: estimated at 1.3 Korean chars or 4 Latin chars per token
Text prompts use measured counts from a local Qwen2.5-14B run
One image ≈ 1,290 tokens on Gemini image models
Video and music bill per second, not per token

✅ Verification

Public result: several real outputs published by outlets or creators
Tested locally: text and settings prompts run on a local model to confirm format and intent
Translated prompts keep the original text under "Original text"

⚖️ Licensing and takedowns

Verbatim prompts come only from sources that permit redistribution (CC0, MIT, CC BY 4.0, official docs, public posts); each entry names its license and creator
Prompts reported by commercial outlets were rewritten by the editors with the same function; the source link is a reference, not a quotation
Result images are the creators' published outputs under their licenses; images showing identifiable real people are not included. Trademarks and characters appear for illustration and belong to their owners
Rights holders can request removal via Contact; we take it down on confirmation
Entries marked "written by Builderlog" are © Builderlog. Personal, non-commercial use in your own agent only. No commercial use and no copying, reposting or redistributing the text in whole or in part (blogs, social media, courses and paid materials included). Share by linking to the entry page. A license stated on the entry takes precedence

📡 Inbox

scripts/collect.py pulls GitHub search, collection READMEs and Hacker News into inbox.json (no LLM)
Runs daily; first-seen items are marked NEW
Inbox items are unverified until promoted into the dex