#4.23 / 31 rate

Steam Booster Packs Profit Finder

1,000 users

2019-08-31

16ROCK

sergey.trush.1994@gmai...

Extension Information

5 star

73%

4 star

3 star

2 star

1 star

15%

Supported Languages

Permissions

Description

Profitably exchange your gems for booster packs from your collection of games

Our Extension helps you see the sale price of booster packs from your Steam library for profit or to recoup some or all of the cost of a purchased game.

Extension functions:
* The "Profit" and "Fast Profit" buttons sort booster packs by price relative to gem value by profit
* "Profit" shows the best starting prices for the sale
* "Fast Profit" shows the best request prices for an instant sale
* Sorting by: name, gems, price and request
* Displaying a color scale on prices to show the profitability of crafting booster packs
* Displays the remaining time until the next booster pack is received when hovering over it (new booster pack become available for exchange every 24 hours)

Get the most out of your game library!

Reviews

William César Santos Ramalho

Falta ainda uma opção de classificar a lista de acordo com o número de vendas em um determinado período (últimas 24 h, uma semana, um mês, um ano, por exemplo), outra opção de classificar de acordo com o preço médio em um determinado período (últimas 24 h, uma semana, um mês, um ano, por exemplo), uma coluna com o valor médio da venda em um determinado período (últimas 24 h, uma semana, um mês, um ano, por exemplo) com o mesmo sistema de cores das outras colunas.

Yegor Sheludko

Extension doesn't work - endless loading.

Cody Johnson

This seems to function well with smaller libraries throughout my testing. However with larger libraries, you will experience issues with prices not being loaded. This is likely due to sending too many requests. This extension would be off the wall if the following areas were considered: 1) Throttling Requests: Potentially introduce delays between requests. 2) Batch Requests: Instead of making individual requests for each item, consider batching requests where possible. 3) Implement caching mechanisms to store previously fetched data locally. This can help minimize redundant requests. 4) Implement error handling to determine if the user is rate-limited.