Save Telegram Reply to Journal Spreadsheet

This workflow automates the collection and updating of LinkedIn contact information. It is triggered on a schedule to read personal profile URLs from Google Sheets, utilizes the Prospeo.io API to query detailed information (such as name, email, position, etc.), and writes the data back to Google Sheets. This process effectively addresses the tediousness of manually searching for contact information, enhances data completeness and accuracy, and simplifies data maintenance. It is suitable for scenarios where sales, business development, and recruitment teams need to quickly obtain contact information.

This workflow automatically retrieves monthly time tracking reports from Clockify and backs up the data to a GitHub repository. It supports data backups for the last three months and can intelligently update existing files or create new ones, ensuring the integrity and accuracy of the data. By performing regular backups, it mitigates the risk of time tracking data being lost due to online changes, making it suitable for individuals and teams that prioritize data security and version control, thereby enhancing management efficiency and reliability.

This workflow provides personalized drinking reminders through scheduled alerts and intelligent message interactions, helping users develop good hydration habits. Users can quickly log their water intake via Slack, with the data automatically synced to Google Sheets for centralized management and analysis. By incorporating health content generated by OpenAI, the reminders are enhanced in professionalism and encouragement. Additionally, data linkage with health applications is achieved through iOS shortcuts, optimizing the user's health management experience.

This workflow automatically reads YouTube video links from Google Sheets, captures comment data in real-time, and uses an AI model to perform sentiment analysis on the comments, classifying them as positive, neutral, or negative. The analysis results are updated back to Google Sheets, ensuring consistency and timeliness in data management. By supporting pagination for comment retrieval and allowing flexible update frequencies, it greatly enhances the ability of content creators and brand teams to gain insights into audience feedback, helping to optimize content strategies and market responses.

This workflow automatically renames specified key names in a set of initial data through a manual trigger function, helping users quickly achieve data field conversion and standardization. It is suitable for use in scenarios such as development debugging and data preprocessing, effectively addressing the issue of inconsistent field naming. This reduces the tediousness of manual modifications, enhances the efficiency and accuracy of data organization, and facilitates the use of subsequent processes.

This workflow automatically processes nested lists by receiving data from external POST requests, generates Excel format spreadsheet files, and directly returns them to the requester. It aims to quickly convert complex API data into an easily viewable and analyzable format, addressing the cumbersome issues of manual organization and format conversion. It is suitable for developers, analysts, and business scenarios that require automated data export, thereby improving work efficiency.

This workflow integrates multiple APIs from CoinMarketCap to create an intelligent agent tool that helps users conduct in-depth queries and analyses of cryptocurrency exchange information and market sentiment. It supports multi-dimensional data retrieval, including exchange details, asset status, and the Fear and Greed Index. By incorporating the GPT-4o Mini model, it enables natural language interaction, enhancing the efficiency and accuracy of data acquisition while lowering the barrier for users to access key information. It is suitable for investors, analysts, and community operators.

This workflow can automatically scrape content from multi-page websites, supporting the retrieval of all site page links through sitemap.xml. It intelligently filters web pages based on specified themes or keywords, extracting titles and the main content in Markdown format. The results are saved to Google Drive for unified management and archiving. It simplifies the traditional web scraping process, eliminating the need for API keys, making it suitable for various scenarios such as content operations, data analysis, and market research. This enhances information collection efficiency and lowers the technical barrier.