WorkBuddy Gift Claimer Daily Points and Check-in Assistant

Problems to Solve

In daily digital interactions, users often need to manually log into multiple platforms (such as WorkBuddy, Alipay, JD.com) to claim points or check-in rewards. This process is repetitive and time-consuming, easily leading to omissions due to neglect, which hinders point accumulation. Manual operations can also become frustrating with interface updates, where buttons may be hard to find. For instance, WorkBuddy offers 150 general points daily, but users might forget to claim them; similar check-in mechanisms on other APPs require regular clicks to avoid reward expiration.

How the Skill Works

Core Capabilities

WorkBuddy Gift Claimer is an AI-driven automation tool designed to address these pain points. Its core capabilities include:

• Automated Recognition and Claiming: Uses pyautogui to simulate mouse operations, combined with OCR (Optical Character Recognition) technology, to automatically detect buttons like "claim," "check-in," or "GO" on the screen and click them, enabling hands-free reward claiming.
• Self-Learning Mechanism: By providing screenshots or videos, the skill can learn new operational scenarios. For example, taking a screenshot of an APP's check-in page allows the skill to extract button positions and text, generating and saving configurations for one-time learning with long-term use. It adapts to minor interface changes, such as button relocation.
• Scheduling and Compensation: Supports installing scheduled tasks (e.g., via trigger word 每天自动领), setting up daily automatic runs. If claiming fails, the skill retries three times and automatically compensates for missed claims upon boot, forming a triple safety net against omissions.

Key Steps

Using this skill typically involves the following key steps:

1. Trigger Execution: Directly say trigger words like 领积分 or 领取礼包, and the skill automatically launches or detects the target app (e.g., WorkBuddy), performs OCR scanning on the screen, identifies and clicks buttons, then outputs the claiming result.
2. Learn New Scenarios: For other platforms, provide clear screenshots (requiring legible text, complete buttons, resolution ≥ 720×1280) or record operation videos (10~60 seconds). After analysis, the skill automatically records newly discovered button text, generates a configuration summary, and allows direct triggering thereafter.
3. Install Scheduled Tasks: Through trigger words like 开机自动领取, the skill sets up Windows Task Scheduler for daily or boot-time automatic claiming, with status checks available (e.g., trigger word 今天领了吗).

The workflow is: receive user instruction → launch or detect target app → execute OCR screen scanning → identify and click buttons → verify results → output formatted status (e.g., success or failure reasons).

Applicable Boundaries and Notes

Despite its practical features, there are clear limitations and considerations:

• System Limitation: Only supports Windows 10/11 operating systems, as it relies on pyautogui for desktop automation. macOS and Linux are incompatible, requiring different technical approaches.
• Dependencies: First run requires internet access to download the OCR model (about 200MB), which may be affected by network conditions. OCR recognition depends on screen resolution; standard aspect ratio coordinates are recommended.
• Learning Requirements: Screenshots or videos must be clear, containing complete button areas. Blurred, truncated, or complex background images may cause learning failures; the skill has adaptive mechanisms, but significant interface changes may require relearning.
• Privacy and Security: All data (e.g., learning configurations) are stored locally and not uploaded to the cloud, but users must ensure operations comply with platform terms to avoid violations.

In summary, this skill simplifies daily point claiming through automation, but users should note its Windows-exclusive nature and learning conditions for reliable use.