> For the complete documentation index, see [llms.txt](https://pandafarm.gitbook.io/pandafarm/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://pandafarm.gitbook.io/pandafarm/asset-management/game-play.md). # Game Play The basic idea of "Play to Earn" at Panda Farm is to encourage pandas to play more games, experience the fun of the game and get more bamboos by winning competitions and participating in missions, and buying more pandas from the bamboos won to improve the panda's battle. Strive to make more money. The game structure of Panda Farm is that different games have different weights to obtain bamboo, and the way to obtain it is also different. It is not a direct and simple digging of bamboo. The game smart contract of Panda Farm is based on a series of algorithms. The dimension of the algorithm includes Panda NFT. The basic attributes, item attributes, number of NFT participation in the game, total number of bamboo tokens, number of panda NFT treatments, parental combat power, and so on. If the same NFT participates in the game more frequently, the mining ability should be weaker to encourage users to snap up new Panda NFTs. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://pandafarm.gitbook.io/pandafarm/asset-management/game-play.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.