# How it works?

Cherry AI Raiding feature is designed for a smooth and easy experience, making community engagement both efficient and effective. With a clean visual interface and simplified steps, it enables projects to drive social activity on X (Twitter) and TikTok with just a few quick actions. By turning engagement into a game-like experience, the raiding feature motivates communities to actively support their favorite projects, helping them gain visibility and climb the Raid Leaderboard.

1. **Starting a Raid**:\
   An admin can initiate a raid by typing the command **/raid** in the Telegram group.
2. **Inserting the Link**:\
   After the command, the admin will be prompted to insert the link to the X (Twitter) or TikTok post they want the community to engage with.
3. **Setting Engagement Goals**:\
   The admin sets the desired number of actions for the raid — including likes, comments, retweets, and bookmarks. These goals determine how many engagements the post should receive.
4. **Earning Points**:\
   Once the community reaches the engagement goals, the project earns points towards the Raid Leaderboard:
   * **Likes**: 0.2 points
   * **Comments**: 0.3 points
   * **Retweets**: 0.2 points
   * **Bookmarks**: 0.2 points
5. **Climbing the Leaderboard**:\
   The more points your project earns, the higher it climbs on the Raid Leaderboard. Higher positions on the leaderboard offer increased visibility and attention within the Cherry AI ecosystem.
6. **Point Expiration**:\
   Points earned from raids expire after **24 hours**, encouraging consistent and active engagement to maintain leaderboard rankings.

By participating in raids, projects can maximize their reach and community involvement while competing for top visibility on the Raid Leaderboard.


---

# Agent Instructions: 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:

```
GET https://docs.cherrybot.co/cherry-raiding/how-it-works.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.