GoalQuest

Main functions:

1. Task creation/joining:

- Task types:

- *Classic tasks: daily habit-forming tasks such as reading, learning foreign languages, and fitness.

- *Web3 tasks: Web3 skill learning tasks such as learning Solidity, understanding DeFi protocols, and participating in DAO governance.

- Challenge tasks: Periodic challenges, such as "30-day writing challenge", "7-day meditation challenge", etc.

- Custom tasks: Users can freely create tasks, set task descriptions, check-in standards, required number of staked tokens, etc.

- Task details:

- Clear task description: Describe task goals, participation requirements, check-in standards, cycles, rewards, and other information in detail.

- Tag system: It is convenient for users to search and filter tasks of interest, such as "#Reading", "#Web3", and "#Fitness".

- Preview mode: Before joining a task, users can view the information of other participants and past check-in records.

- Task matching:

- Smart recommendation: Recommend suitable tasks based on user interests and past participation records.

- Custom filtering: Users can filter by task type, difficulty, cycle and other conditions.

- Friend invitation: Users can invite friends to join the same task.

- Joining process:

- Staking tokens: Users need to stake a certain number of tokens to join the task.

- Confirming the contract: After the user joins the task, a smart contract will be signed to ensure the security of the pledged funds.

2. Daily check-in:

- Diversified check-in methods:

- Text records: Daily record of learning/practical experience and progress.

- Picture/video upload: Upload relevant photos or videos to prove the completion of the task.

- Third-party data access: Connect to health apps such as Strava and Google Fit to automatically synchronize fitness data.

- NFT voucher check-in: After the user completes the daily task, he will receive a daily check-in NFT.

- AI evaluation:

- Text evaluation based on natural language processing: AI analyzes the user's text description to determine whether the check-in requirements are met.

- Picture/video evaluation based on image recognition: AI analyzes the content of the picture/video to determine whether it meets the check-in standards.

- Data Verification: Verify whether third-party data is consistent with the task objectives.

- AI Scoring: Score each check-in, give feedback and suggestions, and help users complete tasks better.

- Check-in Reminder:

- Customized Reminder Time: Users can set a daily check-in reminder time to avoid missing a check-in.

- Push Notification: Send push notifications to remind users to check in.

- Make-up Check-in Mechanism:

- Limited number of make-up check-in opportunities: Allow users to make-up check-ins within a certain period of time, but a small amount of tokens will be deducted.

3. Peer Review (3-Peers Review):

- Review Mechanism: If a user disagrees with the AI ​​evaluation results, he or she can initiate a review.

- Review Group: Randomly select 3 participants of the same task to form a review group.

- Review Process:

- User-provided evidence: Users can provide additional evidence, such as more detailed descriptions, pictures/videos, etc.

- Group Discussion: Review group members review the evidence submitted by users, discuss, and ultimately vote on whether to complete.

- Arbitration: If the review team disagrees, the platform will arbitrate.

- Review Rewards: Review team members can receive a small amount of token rewards.

4. Reward Distribution:

- Fund Pool: The tokens pledged by all participants constitute the fund pool of the task.

- Reward Rules:

- Full Attendance Reward: Participants who complete all check-ins will share the rewards in the fund pool.

- Partial Completion Reward: Partial rewards are allocated according to the degree of completion.

- Review Team Rewards: Review team members receive rewards based on the number of times they participate in the review.

- Transparency: Reward distribution rules, participant lists, bonus pool balances and other information are open and transparent and recorded on the chain.

- Automatic Distribution: After the task is completed, the reward is automatically distributed to the user's wallet.

- NFT Medal Reward: After the user completes the entire cycle task, he can get an exclusive NFT medal for display.

5. Community Interaction:

- Task Chat Room: Each task has an exclusive chat room to facilitate participants to exchange learning experiences and encourage each other.

- Public discussion area: A public discussion area where all users can participate, share experiences and make suggestions.

- Ranking list: A ranking list is generated based on data such as the number of completed tasks and the length of time participated.

- Social sharing: Users can share their check-in results and task achievements on other social media.

- Follow system: Users can follow other users to understand their task progress.