GitHub and Google Sheets integration

AI-Powered Automatic Timesheet Generator for Google Sheets Stop wasting billable hours on manual time-tracking. AutoTimesheet Pro uses AI to collect emails, meetings, and GitHub work, then writes a clean timesheet straight into Google Sheets. Perfect for developers, consultants, agencies, and remote teams. Get Started with n8n now! 🚀 Key Features Automated Google Sheets time-tracking** — zero spreadsheet prep. AI-generated activity summaries** (≤ 120 chars) via OpenAI GPT-4o-mini. Gmail integration** — logs only important emails, skipping newsletters & no-replies. Google Calendar time logger** — captures confirmed events, duration, and attendees. GitHub commit & PR tracker** — records your commits plus opened/closed PRs. Daily 7 PM cron trigger** (easily adjustable). Month-based sheet creation** — new tab spins up on the first run each month. No-code n8n template* — just connect credentials and tweak one Set Variables* node. 🔌 Easily extensible** — drag-and-drop extra n8n nodes to add Slack, Jira, Notion, Asana, Trello, Toggl, or any other data source you need. 🔍 How It Works Collect — n8n pulls data from Gmail, Google Calendar, and chosen GitHub repos. Clean — filters remove noise (newsletters, irrelevant commits, etc.). Condense — OpenAI rewrites each item into a concise, SEO-friendly description. Write — workflow appends Date, Type, and Description to your Timesheet Google Sheet. Extend — simply insert new n8n nodes (e.g., Slack, Notion, Jira) and merge them into the same pipeline. 📈 Benefits for SEO-Minded Professionals Keyword-rich activity log** improves internal search and reporting. Structured data** in Sheets simplifies export to accounting or PM tools. Consistent naming** (CALENDAR_EVENT, EMAIL, COMMIT, PR) makes analytics easy. ✅ Why Choose AutoTimesheet Pro? Zero manual entry — just open the sheet and bill clients. Immediate visibility into where your hours went. Works with any GitHub repo list and any inbox you own. 100 % no-code setup — activate in minutes. Built on n8n, so you can customize and scale without limits. 📥 Get Started Ready to replace manual time-tracking with smart automation? https://n8n.partnerlinks.io/ds9podzjls6d Join N8N now, connect your Google & GitHub accounts, and let AI handle your daily log.

🧠 Automated Resume & Cover Letter Generator This project is an automation workflow that generates a personalized resume and cover letter for each job listing. 🚀 Features Automated Resume Crafting Generates an HTML resume from your data. Hosts it live on GitHub Pages. Converts it to PDF using Gotenberg and saves it to Google Drive. Automated Cover Letter Generation Uses an LLM to create a tailored cover letter for each job listing. Simple Input Database Agent Stores your experience in an n8n Data Table with the following fields: role, summary, task, skills, tools, industry. The main agent pulls this data using RAG (Retrieval-Augmented Generation) to personalize the outputs. One-Time GitHub Setup Initializes a blank GitHub repository to host HTML files online, allowing Gotenberg to access and convert them. 🧩 Tech Stack Gotenberg** – Converts HTML to PDF GitHub Pages** – Hosts live HTML files n8n** – Handles data tables and workflow automation LLM (OpenAI / Cohere / etc.)** – Generates cover letters Google Drive** – Stores the final PDFs ⚙️ Installation & Setup Create a GitHub Repository This repo will host your HTML resume through GitHub Pages. Set the Webhook URL In the notify-n8n.yml file, replace: role | summary | task | skills | tools | industry Create the n8n Data Table Add the following columns: role | summary | task | skills | tools | industry Create a Google Spreadsheet Add these columns: company | cover_letter | resume Install Gotenberg Follow the installation instructions on the Gotenberg GitHub repository: https://github.com/thecodingmachine/gotenberg Customize the HTML Template Modify the HTML resume to your liking. You can use an LLM to locate and edit specific sections. Add Authentication and Link Your GitHub Repo Ensure your workflow has permission to push updates to your GitHub Pages branch. Run the Workflow Once everything is connected, trigger the workflow to automatically generate and save personalized resumes and cover letters. 📝 How to Use Copy and paste the job listing description into the Telegram bot. Wait for the "Done" notification before submitting another job. Do not use the bot again until the notification appears. The process usually takes a few minutes to complete. ✅ Notes This workflow is designed to save time and personalize your job applications efficiently. By combining n8n automation, LLMs, and open-source tools like Gotenberg, you can maintain full control over your data while generating high-quality resumes and cover letters for every job opportunity.

Automatically Assign Categories and Tags to Blog Posts with AI This workflow streamlines your content organization process by automatically analyzing new blog posts in your GitHub repository and assigning appropriate categories and tags using OpenAI. It compares new posts against existing entries in a Google Sheet, updates the metadata for each new article, and records the suggested tags and categories for review — all in one automated pipeline. Who’s It For Content creators and editors** managing a static website (e.g., Astro or Next.js) who want AI-driven tagging. SEO specialists** seeking consistent metadata and topic organization. Developers or teams** managing a Markdown-based blog stored in GitHub who want to speed up post curation. How It Works Form Trigger – Starts the process manually with a form that initiates article analysis. Get Data from Google Sheets – Retrieves existing post records to prevent duplicate analysis. Compare GitHub and Google Sheets – Lists all .md or .mdx blog posts from the GitHub repository (piotr-sikora.com/src/content/blog/pl/) and identifies new posts not yet analyzed. Check New Repo Files – Uses a code node to filter only unprocessed files for AI tagging. Switch Node – If there are no new posts, the workflow stops and shows a confirmation message. If new posts exist, it continues to the next step. Get Post Content from GitHub – Downloads the content of each new article. AI Agent (LangChain + OpenAI GPT-4.1-mini) – Reads each post’s frontmatter (--- section) and body. Suggests new categories and tags based on the article’s topic. Returns a JSON object with proposed updates (Structured Output Parser) Append to Google Sheets – Logs results, including: File name Existing tags and categories Proposed tags and categories (AI suggestions) Completion Message – Displays a success message confirming the categorization process has finished. Requirements GitHub account** with repository access to your website content. Google Sheets connection** for storing metadata suggestions. OpenAI account** (credential stored in openAiApi). How to Set Up Connect your GitHub, Google Sheets, and OpenAI credentials in n8n. Update the GitHub repository path to match your project (e.g., src/content/blog/en/). In Google Sheets, create columns: FileName, Categories, Proposed Categories, Tags, Proposed Tags. Adjust the AI model or prompt text if you want different tagging behavior. Run the workflow manually using the Form Trigger node. How to Customize Swap OpenAI GPT-4.1-mini for another LLM (e.g., Claude or Gemini) via the LangChain node. Modify the prompt in the AI Agent to adapt categorization style or tone. Add a GitHub commit node if you want AI-updated metadata written back to files automatically. Use the Schedule Trigger node to automate this process daily. Important Notes All API keys and credentials are securely stored — no hardcoded keys. The workflow includes multiple sticky notes explaining: Repository setup File retrieval and AI tagging Google Sheet data structure It uses a LangChain memory buffer to improve contextual consistency during multiple analyses. Summary This workflow automates metadata management for blogs or documentation sites by combining GitHub content, AI categorization, and Google Sheets tracking. With it, you can easily maintain consistent tags and categories across dozens of articles — boosting SEO, readability, and editorial efficiency without manual tagging.

Who's it for Open-source maintainers, product teams with public repositories, and any organization receiving a steady stream of GitHub Issues. Ideal for small teams who waste hours per week triaging duplicates and misrouted reports. How it works When a new Issue is opened, a GitHub webhook fires this workflow. It first filters for the "opened" action, then fetches the last 30 Issues from the repository. All Issue texts (new + past) are sent to OpenAI's embeddings API in a single batch call for efficiency. The workflow calculates cosine similarity between the new Issue and every past Issue. If the maximum similarity exceeds 0.85, the new Issue is auto-closed with a comment referencing the original. Otherwise, AI classifies it into one of four categories: bug (adds label + Slack alert to dev team), question (posts FAQ link as a comment), feature (appends to a roadmap Google Sheet), or spam (auto-close with label). AI is used only for classification — the duplicate detection uses deterministic vector math, and every action is rule-based. Set up steps Generate a GitHub Personal Access Token with repo scope Create a webhook on your repository pointing to this workflow's URL, subscribing to Issues events Create a Google Sheet named feature_roadmap with columns: date_added, issue_number, title, author, url, status Open Set Configuration and fill in the repo owner, repo name, Sheet ID, Slack channel, and FAQ URL Register GitHub and OpenAI Header Auth credentials and connect Google Sheets and Slack Activate the workflow How to customize Adjust duplicate_threshold for stricter or looser matching, change the embeddings model, or swap Sheets for Notion or Airtable.

How it works This workflow automatically handles new GitHub issues by reading and understanding them using AI, then taking multiple actions simultaneously — creating tasks, sending notifications, and keeping everything organized — without any manual effort. Step-by-step Trigger & filter** GitHub Trigger – Listens for issue events on a GitHub repository. If – Filters to only process issues with the action opened. AI analysis** Message a model – Sends the issue title, body, and metadata to GPT-4.1-mini with a structured prompt to extract category, subcategory, severity, priority, estimated effort, assigned team, summary, and suggested action. Parse AI Response – Converts the raw AI text output into a clean structured JSON object and appends a formatted date. Parallel output actions** Append row in sheet – Logs all issue data and AI analysis into a Google Sheets tracker. Create a task – Creates a prioritized ClickUp task with full issue and AI analysis details. Send a message – Posts a formatted Slack alert to #github-alerts with issue details and AI analysis. Send a message1 – Sends an HTML-formatted email via Gmail with the full issue report and AI insights. Create a comment on an issue – Posts the AI analysis summary as a comment directly on the GitHub issue. HTTP Request – Applies AI-generated labels (category + severity) to the GitHub issue via the GitHub API. Why use this? Eliminates manual issue triage by using AI to instantly classify and prioritize every new issue Keeps the entire team informed across Slack, Email, and GitHub simultaneously Auto-creates ClickUp tasks so nothing falls through the cracks Logs every issue to Google Sheets for reporting and trend analysis Responds directly on GitHub so issue reporters get instant acknowledgment

Deliver your product updates in a modern, accessible format. This workflow automatically transforms GitHub releases into podcast-style audio announcements and distributes them via email and Slack. 🎯 What This Workflow Does This template bridges your development cycle with your marketing and communication channels. 🐙 Step 1 — GitHub Trigger & Notion Synthesis GitHub Trigger:** Fires when a new release is published Parsing:** Converts raw markdown into structured categories (features, fixes, improvements) Notion Merge:** Enriches data with additional context from your Notion changelog database 🎙️ Step 2 — AI Scriptwriting & Professional TTS Script Generation:** OpenAI converts technical notes into a conversational 60–90 sec script Voice Generation:** ElevenLabs turns the script into high-quality audio CDN Hosting:** Uploads MP3 via UploadToURL to generate a public URL 📧 Step 3 — Multimedia Newsletter Delivery Subscriber Fetch:** Loads email list from Google Sheets Email Creation:** Builds a rich HTML email with embedded audio player Distribution:** Sends via Gmail using BCC list 💬 Step 4 — Internal Sync & Database Update Slack Alert:** Posts update with audio preview to team channel Notion Update:** Marks entry as published and stores audio URL ✨ Key Features Bidirectional Notion Sync:** Reads and updates changelog entries Conversational AI:** Converts technical updates into human-friendly audio Dynamic HTML Emails:** Includes inline audio playback High-Quality Voice:** Uses ElevenLabs for realistic narration 🔧 Setup Requirements Required Integrations GitHub:** Personal Access Token (repo read scope) Notion:** Integration token + changelog database ElevenLabs:** API key + Voice ID OpenAI:** API key UploadToURL:** For MP3 hosting Slack:** Bot token Environment Variables NOTION_DATABASE_ID APPROVER_EMAIL DISCORD_WEBHOOK_URL SLACK_CHANNEL_ID Humanize your software updates. Import this template and start broadcasting your product journey with audio.