Workflow Templates

Overview AI-powered SRE sub-workflow that investigates user-reported incidents coming from a Mattermost channel and posts a structured diagnostic report back into the same thread. The result is a four-section incident report: What happened — a concise summary of the symptoms Event timeline — what was happening in the 10+ minutes before the incident Root cause — up to two probable causes Troubleshooting tips — step-by-step remediation for each root cause Requirements OpenRouter/OpenAI/Anthropic API key Google Gemini API key — for embeddings Mattermost API credentials — to post the reply back to the channel Qdrant instance Remote MCP servers (see MCP section) A sub-workflow that analyses attachments A parent workflow that triggers this one via "Execute Workflow" with a properly shaped payload How it works The workflow is triggered by another workflow (When Executed by Another Workflow) ReadIncidentContext logs the incoming classification for debugging and forwards the payload downstream Call 'attachmentsAnalyzer invokes a vision sub-workflow with the file_ids SetVars defines the configuration used by the AI Agent prompt AI Agent runs the investigation Post a message` sends the agent's final output back to the originating channel How to use Prepare the knowledge base — upload your infrastructure description, service map, naming conventions and runbooks into a Qdrant collection Deploy the MCP servers and put their URLs into the corresponding tool Configure credentials Adjust the configuration in SetVars Plug in the attachments sub-workflow — replace the workflow reference in Call 'attachmentsAnalyzer' with your own vision-analysis workflow that maps file_ids[] Tune the system prompt in the AI Agent — add project-specific naming conventions, ownership info, escalation rules and any quirks of your infrastructure Connect classification workflow as parent

Description: Turn your n8n workflow into an automated competitive intelligence unit. This template monitors competitor activities across blog feeds and YouTube channels to detect strategic shifts. Instead of simply aggregating links, it uses Apify to fetch full video transcripts and Google Gemini to analyze the content's underlying message, tone, and positioning. The final output is a structured strategic briefing sent to Telegram and archived in Notion for long-term research. Who is this for This workflow is designed for market researchers, founders, and content strategists who need deep insights into competitor activities without manually scrubbing video timelines or reading daily blog posts. How it works Ingest: The workflow pulls the latest articles from configured RSS feeds and searches for new videos on specific YouTube channels. Deep Dive: It automatically triggers an Apify actor to scrape the full transcript of any new video, ensuring the AI analyzes the spoken content rather than just metadata. Analyze: Google Gemini processes the consolidated text to identify core messages, hidden strategies, and suggests potential counter-tactics. Report: Telegram:** Delivers a concise HTML executive summary with direct source links. Notion:** Appends a comprehensive report to a database using formatted Notion Blocks (Headings, Toggles, and Bullet points). Requirements Apify Account:** A free account is sufficient to run the youtube-transcript-scraper. Services:** Google Gemini (PaLM), YouTube Data API, Telegram, Notion. How to set up Credentials: Configure your API keys for YouTube, Apify, Google Gemini, Telegram, and Notion. Notion Setup: Create a new Database with two properties: Name (Title) and date (Date). Copy the Database ID from the URL into the Notion node. Data Sources: Update the Channel ID in the YouTube nodes to track your target competitors. Update the Feed URL in the RSS nodes. How to customize the workflow Scale Up:** To monitor more competitors, duplicate the YouTube or RSS nodes in the "Data Sources" section and connect them to the Merge node. Adjust Analysis:* Modify the system prompt in the *Google Gemini** node to focus on specific intelligence needs (e.g., "Focus on pricing changes" or "Identify new feature releases"). Token Optimization:** Use the configuration in the Code - Data Prep node to limit the number of items processed daily if you are using free-tier API limits. Need Help or Want to Customize This? Contact me for consulting and support: Email: cuongnguyen@aiops.vn

How it works This template is an end-to-end demo of a chatbot using business data from multiple sources (e.g. Notion, Chargebee, Hubspot etc.) with RAG + SQL. Peliqan.io is used as a "cache" of all business data. Peliqan uses one-click ELT to sync all your business data to its built-in data warehouse, allowing for fast & accurate RAG and "Text to SQL" queries. The workflow will write source data to Supabase as a vector store, for RAG searches by the chatbot. The source URL (e.g. the URL of a Notion page) is added in metadata. The AI Agent will decide for each question to use either RAG or Text-to-SQL or a combination of both. Text-to-SQL is performed via the Peliqan node, added as a tool to the AI Agent. The question of the user in natural language is converted to an SQL query by the AI Agent. The query is executed by Peliqan.io on the source data and the result is interpreted by the AI Agent. RAG is typically used to answer knowledge questions, often on non-structured data (Notion pages, Google Drive etc.). Text-to-SQL is typically used to answer analytical questions, for example "Show list of customers with number of open support tickets and add customer revenue based on invoiced amounts". Preconditions You signed up for a Peliqan.io free trial account You have one or more data sources, e.g. a CRM, ERP, Accounting software, files, Notion, Google Drive etc. Set up steps Sign up for a free trial on peliqan.io: https://peliqan.io Add one or more sources in Peliqan (e.g. Hubspot, Pipedrive...) Copy your Peliqan API key under settings and use it here to add a Peliqan connection Run the "RAG" workflow to feed Supabase, change the name of the table in the Peliqan node "Get table data". Update the list of tables & columns that can be used for SQL in the System Message of the AI Agent. Visit https://peliqan.io/n8n for more information. Disclaimer: This template contains a community node and therefore only works for n8n self-hosted users.

Description: Overview This workflow generates automated revenue and expense comparison reports from a structured Google Sheet. It enables users to compare financial data across the current period, last month, and last year, then uses an AI agent to analyze and summarize the results for business reporting. Prerequisites A connected Google Sheets OAuth2 credential. A valid DeepSeek AI API (or replaceable with another Chat Model). A sub-workflow (child workflow) that handles processing logic. Properly structured Google Sheets data (see below). Required Google Sheet Structure Column headers must include at least: Date, Amount, Type. Setup Steps Import the workflow into your n8n instance. Connect your Google Sheets and DeepSeek API credentials. Update: Sheet ID and Tab Name (already embedded in node: Get revenual from google sheet). Custom sub-workflow ID (in the Call n8n Workflow Tool node). Optionally configure chatbot webhook in the When chat message received node. What the Workflow Does Accepts date inputs via AI chat interface (ChatTrigger + AI Agent). Fetches raw transaction data from Google Sheets. Segments and pivots revenue by classification for: Current period Last month Last year Aggregates totals and applies custom titles for comparison. Merges all summaries into a final unified JSON report. Customization Options Replace DeepSeek with OpenAI or other LLMs. Change the date fields or cycle comparisons (e.g., quarterly, weekly). Add more AI analysis steps such as sentiment scoring or forecasting. Modify the pivot logic to suit specific KPI tags or labels. Troubleshooting Tips If Google Sheets fetch fails: ensure the document is shared with your n8n Google credential. If parsing errors: verify that all dates follow the expected format. Sub-workflow must be active and configured to accept the correct inputs (6 dates). SEO Keywords (ẩn hoặc mô tả ngầm): Google Sheets report, AI financial report, compare revenue by month, expense analysis automation, chatbot n8n report generator, n8n Google Sheet integration

Quick overview This workflow listens for Jira issue create/update events, finds unassigned issues in a target project, pulls team member data from Airtable plus each member’s open Jira workload, and uses an OpenRouter-powered AI agent to choose an assignee and update the Jira issue. How it works Triggers from Jira on issue creation or issue update. Sets the target Jira project key, then fetches all issues for that project from Jira and the matching team roster from Airtable. Filters the Jira results to keep only issues with no assignee and stops if there are no issues to process. Iterates through each unassigned issue and, for each team member from Airtable, queries Jira for their non-DONE issues to capture current workload. Consolidates the team roster and workload details into a single payload tied to the current issue key. Uses an OpenRouter chat model–backed AI agent (with Jira Issue lookups) to select the best Jira accountId and return a structured JSON decision with a reason. Updates the Jira issue by setting its assignee to the chosen accountId, then continues to the next unassigned issue. Setup Add credentials for Jira Software Cloud, Airtable Personal Access Token, and OpenRouter. In Airtable, create or map a team members table that includes the fields used by the workflow (including Jira_Project_Key and Jira_Account_Id) and set the correct base/table in the Airtable search step. Update the JIRA_PROJECT_KEY value to the Jira project you want to manage and ensure the Airtable filter matches that key. Enable a Jira webhook/trigger connection for issue_created and issue_updated events and activate the workflow.

This intelligent workflow automates the entire lifecycle of behavior-driven email marketing — from real-time event capture to hyper-personalized campaign delivery. By continuously tracking user actions on your website and across email interactions, the system identifies high-value behavioral patterns, segments users dynamically, and generates contextually relevant emails using AI. Instead of sending generic broadcasts, this workflow enables true 1:1 personalization at scale, dramatically improving open rates, click-through rates, and revenue per email. Who’s it for E-commerce brands** looking to recover abandoned carts and drive repeat purchases SaaS & subscription companies** focused on user activation, engagement, and retention Growth and performance marketing teams** running sophisticated behavioral campaigns Companies with high website traffic and sizable email lists who want to move beyond basic segmentation Teams that want to leverage AI to create personalized messaging without manual copywriting for every segment How it Works The workflow is divided into three core phases: 1. Event Triggers & Intake Captures real-time events via webhooks (website actions, email engagements, etc.) Processes a Daily Behavior Digest for users with ongoing activity Prepares rich event context and runs initial Python-based behavioral segmentation Normalizes and enriches incoming data for downstream analysis 2. Behavior Analysis & Segmentation Applies intelligent filters to identify key behavioral cohorts: High Intent users (strong purchase signals) Abandoned Cart users Re-engagement opportunities (dormant or at-risk users) Uses rate limiting to maintain system stability Leverages OpenAI’s Chat Model to analyze user behavior and generate deeply personalized email content Formats the final campaign payload with JavaScript for delivery 3. Personalization & Campaign Execution Sends highly personalized emails through your ESP (SendGrid, Mailgun, etc.) Implements smart send buffering for optimal timing and deliverability Logs every campaign to Google Sheets (or your chosen database) for performance tracking and CRM enrichment Closes the loop by feeding outcomes back into user profiles for future segmentation Key Benefits Hyper-personalization** powered by AI that understands user context Reduced manual workload — campaigns are generated and sent automatically Better timing through behavioral triggers and send buffering Full visibility and attribution with campaign logging and tracking pixels Scalable architecture that grows with your traffic and customer base Setup Instructions Import the workflow into your automation platform Configure credentials for: Webhooks (incoming events) Email Service Provider (SendGrid, Mailgun, etc.) Google Sheets / Airtable / CRM OpenAI API Customize segmentation rules and prompt templates to match your brand voice Connect tracking pixels and UTM parameters for end-to-end measurement Test with your key behavioral segments (Abandoned Cart, High Intent, etc.) Requirements Website event webhooks (GA4, custom pixel, Segment.com, or RudderStack) Email service with strong webhook & API support User database or CRM synchronization Access to an AI model (OpenAI GPT-4o or equivalent)

Quick overview Turn Microsoft Teams into a natural language BI tool. This dual-agent Claude workflow intelligently classifies user questions, generates safe BigQuery SQL, executes the query, and returns a plain-English summary alongside a data preview directly to your Teams channel. How it works The workflow listens for new messages in a designated Microsoft Teams channel or chat. It checks a 24-hour static data cache for your BigQuery schema. If the cache is missing or expired, it automatically fetches the latest INFORMATION_SCHEMA metadata. A main Claude 3.5 Sonnet agent classifies the user's intent (analytical, conversational, or unsafe) and identifies the relevant database tables. If the intent is analytical, a specialized Claude SQL sub-agent generates a read-only SELECT query tailored exactly to your schema. The workflow executes the query against BigQuery (safely constrained to a maximum of 100 rows). A final Claude agent translates the raw query results into a concise, plain-English summary. The answer is posted back to Teams as an Adaptive Card, complete with a formatted data preview and the generated SQL code. Non-analytical questions or pipeline errors are intelligently routed to receive standard conversational replies in Teams. Setup CRITICAL SECURITY: Restrict your Google Cloud Service Account IAM roles to BigQuery Data Viewer and BigQuery Job User ONLY. Do not use a highly privileged account. Configure your Microsoft Teams trigger and posting credentials, specifying the target team and channel for the bot to operate in. Configure your Google BigQuery credentials to allow reading metadata and executing queries. Configure your Anthropic credentials for the three Claude LangChain nodes. Update the "Configure Variables" node with your specific GCP Project ID and BigQuery Dataset ID. Requirements A Google Cloud project with BigQuery enabled and existing structured datasets. An Anthropic API key with access to the Claude 3.5 Sonnet model. Microsoft Teams administrator access to authorize the n8n integration. Customization Distributed Environments: If you are running n8n with multiple worker nodes (Queue Mode), you must swap the $getWorkflowStaticData() schema cache logic to read/write from a dedicated Key-Value store (like Redis or Supabase) to ensure state synchronization. UI Layout: Modify the Create Teams Adaptive Card node to add corporate branding, custom colors, or alter the FactSet data preview structure. Additional info This architecture features built-in pipeline protections, including strict 40,000-character payload limits to prevent LLM context window blowouts, and fallback handling for "zero-row" query results to ensure users are never left without a response.

Telegram AI Assistant with Memory, Tasks, and Live Search (Airtable + Google Calendar) This workflow creates an intelligent Telegram-based AI assistant that remembers user details, manages lists, integrates with Google Calendar, and can fetch live information from the web. It is designed for everyday use and improves over time with your feedback. What It Does Personal Memory:** Saves user preferences and instructions in Airtable. Task & Grocery Lists:** Add, search, or delete grocery and to-do items directly in Telegram. Calendar Management:** Create, update, delete, and search events (single or recurring) with Google Calendar. Voice Support:** Send voice messages—these are transcribed and processed like text. Web Search:** (Optional) Fetch real-time answers using SerpAPI. Prerequisites n8n (Cloud or self-hosted instance). Telegram Bot (create via @BotFather on Telegram). Airtable account with a new Base containing 3 tables: User Memory Grocery's To Do List Google Account with Calendar enabled (for OAuth2). OpenAI API Key (for AI responses + voice transcription). SerpAPI Key (optional, for live web search). Airtable Schema Inside your new Airtable Base, create the following tables and fields: User Memory Memory (text) User (text) Time (created time) Grocery's Item (text) User (text) Created (created time) To Do List Task (text) Project or Class (text) User (text) Created (created time) > Field names must match exactly. Setup Instructions Import the workflow JSON into n8n. Configure credentials for each service in the workflow: Telegram API → Paste in your bot token. Airtable → Add your Airtable personal access token. After this, Airtable nodes will show dropdowns where you can select your Base and then your Tables (no need to paste IDs). Google Calendar → Connect your Google account. Once credentials are added, simply pick your Calendar from the dropdown (e.g., “primary” or any shared calendar). OpenAI → Add your API key for chat + voice transcription. SerpAPI → Add your API key (optional). For Telegram Trigger: Click “Listen for Test Event” and send a message to your bot to register the webhook. In group chats: disable privacy mode in @BotFather so the bot can see all messages. Activate the workflow and start chatting with your bot. How to Use Memory** “Remember my coffee order is oat milk latte.” “Keep replies shorter.” Grocery List** “Add eggs.” → “Added eggs.” “What’s on my grocery list?” → Lists all items “Remove bread.” → “Removed bread.” To-Do List** “Add finish report for work.” “What’s on my to-do list?” “Remove finish report.” Calendar** “Create event ‘Team sync’ tomorrow 3–4 pm.” “Make a recurring study session every Friday at 2 pm.” “Delete the dentist appointment at 4 pm.” Web Search** “Get news.” → Summarizes top 5–6 stories from the past 24 hours. Configuration Notes You don’t need to enter Airtable IDs or Calendar IDs manually — just use the dropdowns after credentials are set up. Airtable “User” field is filled automatically with the Telegram username. Voice messages are downloaded and transcribed by OpenAI before being processed as text. Security All API keys and tokens are stored securely in n8n Credentials. No hard-coded IDs, emails, or secrets in this template. Webhook IDs are not included; n8n generates them automatically on import. Troubleshooting Bot not responding?** Ensure the workflow is active, Telegram Trigger is listening, and bot privacy settings are configured for groups. Airtable errors?** Check that your base and tables exist, and that field names match exactly. Calendar issues?** Confirm the Google account has access to the selected calendar. Voice transcription failing?** Verify your OpenAI credentials and Telegram bot permissions. Why This Template Works for Everyone Uses dropdown selections for Airtable and Google Calendar (no IDs needed). Includes clear setup instructions. Credentials are handled securely through n8n. Flexible: works with groceries, tasks, memory, calendar, and optional live web search.

📧 Google Sheets Bulk Email Validator Automatically validate email addresses in Google Sheets using Verify Email This workflow scans your Google Sheets weekly (configurable), finds unverified email addresses, and validates them through the Verify Email API. Results are automatically added back to your spreadsheet 📋 How It Works Reads all email addresses from your Google Sheets Validates email addresses that haven't been verified yet (Status column is empty) Writes results — Valid or Block with the reason for blocking 🔧 Required Google Sheets Setup Your Google Sheet MUST have these column headers in Row 1: | Column | Header | Content | |--------|--------|---------| | A | Email | Email addresses to validate | | B | Status | Validation result: Valid or Block | | C | Reason | Block reason: Invalid, Blacklisted, Disposable | Example table: | | A | B | C | |-----|---|---|---| | 1 | Email | Status | Reason | | 2 | user@example.com | (empty) | (empty) | | 3 | john@company.com | (empty) | (empty) | 🚀 Setup Instructions Step 1: Google Cloud Console Setup (One-time) Go to Google Cloud Console Create a new project (or select existing one) Enable APIs: Search for "Google Sheets API" → Click Enable Search for "Google Drive API" → Click Enable Create OAuth 2.0 credentials: Go to Credentials → Create Credentials → OAuth 2.0 Client ID Select Web application Add authorized redirect URI Copy your Client ID and Client Secret Save these for the next step Log in to your Google account. Select your Google account and grant permissions Verify the connection shows "Account connected" Step 2: Prepare Your Google Sheet Open your Google Sheets file In Row 1, add these exact headers: Cell A1: Email Cell B1: Status Cell C1: Reason Starting from Row 2, add your email addresses in Column A only Leave Column B (Status) empty — workflow will fill it with validation results Leave Column C (Reason) empty — workflow will fill it with block reasons Step 3: Configure Workflow with Your Sheet Details Find your Sheet ID (it's in your Google Sheets URL): docs.google.com/spreadsheets/d/YOUR_SHEET_ID_HERE/edit Update in workflow: Document ID → Paste your Sheet ID Sheet Name → Tab name (default: "Sheet1") Step 4: Get Verify Email API Key Visit verify-email.app Sign up for a free account (50 verifications/month) Go to Dashboard → API Keys Copy your API Key Add it as credential in n8n: Click on "Verify API (Batch)" node in workflow Create new credential: "Verify Email API Key" Paste your API key Save Step 5: Choose Your Trigger The workflow has 3 different triggers: Trigger 1: Scheduled (Weekly) Runs automatically every Monday at 8:00 AM Click "Publish" to enable Edit the Schedule Trigger to change timing Trigger 2: Manual (Execute) Click "Execute workflow" button to run on demand Use this to test or validate emails immediately No scheduling needed Trigger 3: Webhook Trigger validation from external services or apps Send a POST request to the webhook URL Useful for automated integrations To activate: Click "Publish" to enable scheduled runs, then choose additional triggers as needed ✅ How to Use Add email addresses only to Column A (starting Row 2) Leave Column B (Status) and Column C (Reason) empty Workflow runs automatically on schedule or manually Results will appear in Column B (Valid/Block) and Column C (block reason) Already-verified emails are skipped on next runs

Advanced AI Inventory Agent: Supabase Vector RAG & Gemini This workflow upgrades your AI agent from simple sheet reading to high-performance Vector RAG. It allows your assistant to search through thousands of items with lightning speed and high accuracy. Purpose: To provide a scalable, professional-grade retrieval system for hardware inventory. It uses "semantic search" to find products even when the user makes typos or uses different terminology. Setup Instructions: Supabase: Run the provided SQL to create the documents table and the match_documents function. Credentials: Connect your Supabase (Service Role Key) and Google Gemini API credentials. Sync Workflow: Run the "Path A" workflow to index your Google Sheets data into the vector database. Chat Workflow: Use the "Path B" workflow as your production chat interface. Prompt: Customize the System Prompt to define your brand's specific tone and sales rules. Ideal for: Large product catalogs (100+ items), technical hardware inventories, and high-traffic customer support bots. To learn more about how to build and optimize this workflow, read the full blog post here.

How it works An AI-powered sales agent on WhatsApp that handles product inquiries using your Supabase knowledge base and n8n catalog. Customers can send text, voice notes, or images to ask about products, pricing, and specs. The agent responds with detailed answers, product images, and FAQs, creating a complete self-service sales experience. (I primarily designed this for furniture business, consider tailoring it) Setup steps Connect Supabase credentials for your knowledge base and FAQs Configure n8n tables with your product catalog (prices, descriptions, image links) Set up WhatsApp Business API integration Add your product categories and common queries to the AI context Test with sample product questions and image uploads Customization tips Structure your catalog tables with clear columns (SKU, price, description, image_url) Add industry-specific terminology to the AI prompt Create templated responses for common FAQs to ensure consistency Enable voice-to-text transcription for better voice note handling Add product recommendation logic based on customer queries Set up image recognition for customers sending product photos to identify items

Environment Config Diff & Propagate for Android Builds This workflow automatically detects changes in the .env.staging file in a GitHub repository and keeps Android configuration files (build.gradle and gradle.properties) in sync.It creates a new Git branch, applies updates safely, opens a pull request and notifies the team on Slack — all without manual effort. Whenever .env.staging changes: The workflow detects the change via GitHub webhook Compares ENV values with Android config files Automatically updates build.gradle and gradle.properties Creates a new Git branch Opens a pull request Sends a Slack notification You get: Automatic Android config synchronization** Safe updates via pull requests** Zero manual copying of ENV values** Instant Slack visibility for the team** Ideal for teams managing Android app configuration across environments without mistakes. What It Does This workflow automates Android configuration updates end-to-end: Listens for GitHub push events. Checks if .env.staging was modified. Stops execution if ENV file was not changed. Fetches .env.staging and gradle.properties from main. Converts both files into easy-to-compare key-value pairs. Compares ENV values against Gradle values. Creates a new Git branch for changes. Fetches files from the new branch. Identifies which variables must be updated. Applies ENV values to: build.gradle gradle.properties Commits the changes. Creates a pull request. Sends a Slack notification with PR details. This ensures Android configs are always aligned with ENV files. Who’s It For This workflow is ideal for: Android development teams DevOps & platform engineers CI/CD automation teams Teams managing multiple environments (staging / prod) Organizations avoiding manual config drift Anyone tired of copy-pasting ENV values Requirements to Use This Workflow To run this workflow, you need: n8n instance** (cloud or self-hosted) GitHub repository** with: .env.staging app/build.gradle gradle.properties GitHub Personal Access Token** Slack workspace** + API credentials Basic understanding of Android config files How It Works GitHub Webhook TriggerListens for commits pushed to the repository. ENV Change CheckWorkflow continues only if .env.staging changed. Fetch & Parse FilesReads ENV and Gradle files and converts them into key-value format. Compare Config ValuesFinds missing or mismatched variables. Create Safe BranchGenerates a timestamp-based branch from main. Apply UpdatesUpdates only the required values in: build.gradle gradle.properties Commit ChangesSaves updates to the new branch. Create Pull RequestOpens a PR for review. Notify SlackSends PR link and details to the team. Setup Steps Import the provided n8n workflow JSON. Configure GitHub credentials in all GitHub & HTTP nodes. Set your repository name and owner. Configure Slack credentials and select a channel. Ensure .env.staging exists in your repo. Activate the workflow. Push a change to .env.staging — automation starts instantly How To Customize Nodes Customize ENV File Replace .env.staging with .env.production or others. Update filename in GitHub fetch + check nodes. Customize Android Files Extend logic to include: local.properties BuildConfig.kt settings.gradle Customize Branch Naming Modify the Generate New Branch Name node. Add environment names or commit IDs. Customize Slack Message You can add: Emojis PR author name Changed variable list Mentions (@team, @android) Add-Ons (Optional Enhancements) You can extend this workflow to: Support multiple ENV files Add approval checks before PR creation Auto-merge after approval Validate ENV variable formats Send diff summary to Slack Block secrets from being committed Add Jira / Linear ticket creation Trigger Android CI build after PR creation Use Case Examples 1\. Environment Sync Keep Android configs aligned with staging ENV automatically. 2\. CI/CD Safety Prevent broken builds due to mismatched config values. 3\. Team Transparency Everyone sees config updates via Slack + PRs. 4\. DevOps Automation Remove repetitive manual config updates. 5\. Audit Friendly All changes tracked through Git history & PRs. Troubleshooting Guide | Issue | Possible Cause | Solution | |------------------------|----------------------------------|------------------------------------------------------| | Workflow not triggered | Webhook not configured | Re-register GitHub webhook | | No PR created | .env.staging not changed | Ensure the file is modified | | Wrong values updated | Parsing logic issue | Check KEY=VALUE format | | Slack message not sent | Invalid credentials | Reconnect Slack API | | Commit failed | Missing permissions | Check GitHub token scopes | Need Help? If you need help extending or customizing this workflow, adding production support, CI integrations, security checks or enterprise-scale automation, then our n8n workflow development team at WeblineIndia can help you build robust, production-ready workflows.