{ "generatedAt": "2026-05-07T13:26:57.543Z", "total_prompts": 14, "covered": 14, "uncovered": 0, "coverage": 1, "target": 0.7, "passed": true, "results": [ { "prompt_file": "airtable-split-to-slack.json", "prompt": "Every hour, fetch all records from an Airtable table. Use the HTTP Request node to call GET https://api.airtable.com/v0/app123abc/Tasks with a Bearer token auth header — Airtable responds with a JSON ", "keywords": [ "hour", "records", "airtable", "table", "app123abc", "tasks", "bearer", "token", "header", "responds", "json", "object", "shape", "where", "record", "post", "slack", "channel", "daily-tasks", "containing", "task", "status", "later", "build", "schedule", "split" ], "matched": true, "top_match": { "slug": "automate-3d-body-model-generation-from-images-using-sam-3d-g-11460", "matches": 10, "matched_keywords": [ "tasks", "header", "json", "shape", "where", "post", "channel", "task", "status", "schedule" ] } }, { "prompt_file": "contact-form-automation.json", "prompt": "Create a workflow that handles contact form submissions via a webhook. It should send an auto-reply email to the person who submitted the form, notify my team on Telegram, and log each submission to G", "keywords": [ "handles", "contact", "form", "webhook", "auto-reply", "email", "person", "who", "notify", "team", "telegram", "log", "google", "sheets", "documentid", "1bximvs0xra5nfmdkvbdbzjgmuuqptlbs74ogve2upms", "sheet", "later", "build", "gmail", "multi", "action" ], "matched": true, "top_match": { "slug": "lead-generation-system-google-maps-to-email-scraper-with-goo-5385", "matches": 12, "matched_keywords": [ "handles", "contact", "form", "email", "team", "log", "google", "sheets", "sheet", "build", "multi", "action" ] } }, { "prompt_file": "cross-team-linear-report.json", "prompt": "Get all the Linear issues created in the last 2 weeks. Filter them for issues created for a different team than the one the creator is in. I have this team mapping to use: Alice (alice@company.com) be", "keywords": [ "linear", "issues", "created", "last", "weeks", "filter", "different", "team", "than", "creator", "mapping", "alice", "company", "belongs", "both", "frontend", "bob", "backend", "carol", "store", "note", "person", "belong", "multiple", "teams", "cross-team", "issue", "only", "not", "list", "calculate", "number", "tickets", "per", "post", "ordered", "descending", "slack", "channel", "called", "cross-team-reports", "later", "build", "schedule", "processing" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 19, "matched_keywords": [ "linear", "issues", "filter", "different", "team", "company", "note", "multiple", "teams", "issue", "only", "not", "list", "calculate", "number", "per", "channel", "schedule", "processing" ] } }, { "prompt_file": "daily-slack-summary.json", "prompt": "Every day, get the posts made in the past day on 3 different Slack channels: #general (C04GENERAL01), #engineering (C04ENGINEER1), and #product (C04PRODUCT01). Summarize them using AI, and post the su", "keywords": [ "day", "posts", "made", "past", "different", "slack", "channels", "general", "c04general01", "engineering", "c04engineer1", "product", "c04product01", "summarize", "post", "summary", "daily-digest", "c04dailydg01", "later", "build", "schedule" ], "matched": true, "top_match": { "slug": "ai-telegram-bot-agent-smart-assistant-content-summarizer-4457", "matches": 9, "matched_keywords": [ "day", "made", "different", "product", "summarize", "post", "summary", "build", "schedule" ] } }, { "prompt_file": "form-to-hubspot.json", "prompt": "Create a form that collects: name, email, company, and interest level (dropdown: starter, professional, enterprise). When submitted, create a new contact in HubSpot with firstname, lastname (split fro", "keywords": [ "form", "collects", "email", "company", "interest", "level", "dropdown", "starter", "professional", "enterprise", "new", "contact", "hubspot", "firstname", "lastname", "split", "custom", "property", "confirmation", "sendgrid", "address", "subject", "reaching", "body", "mention", "later", "build", "trigger", "crm" ], "matched": true, "top_match": { "slug": "scrape-google-maps-business-leads-with-apify-gpt-4-email-ext-10640", "matches": 13, "matched_keywords": [ "form", "email", "company", "professional", "contact", "hubspot", "split", "custom", "confirmation", "address", "build", "trigger", "crm" ] } }, { "prompt_file": "github-notion-sync.json", "prompt": "Every day, fetch all open GitHub issues from repository 'acme-corp/backend' that have the label 'bug'. For each issue, create a page in a Notion database (database ID: 'a1b2c3d4e5f6789012345678abcdef0", "keywords": [ "day", "open", "github", "issues", "repository", "acme-corp", "backend", "label", "bug", "issue", "page", "notion", "database", "a1b2c3d4e5f6789012345678abcdef01", "properties", "title", "html", "created", "date", "assignee", "login", "unassigned", "status", "directly", "repos", "labels", "state", "bearer", "token", "authorization", "header", "later", "build", "schedule", "sync" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 11, "matched_keywords": [ "day", "open", "issues", "label", "issue", "page", "database", "date", "labels", "header", "schedule" ] } }, { "prompt_file": "linear-bq-leaderboard.json", "prompt": "Every two weeks I want to check the amount of n8n usage and bug reporting that the team has done and produce a leaderboard that then gets posted to Slack (channel ID: D034WT7G4CW).\n\nHere are the users", "keywords": [ "weeks", "want", "check", "amount", "n8n", "usage", "bug", "reporting", "team", "produce", "leaderboard", "posted", "slack", "channel", "d034wt7g4cw", "here", "users", "david", "roberts", "arens", "niklas", "hatje", "example", "last", "jonathan", "clift", "tickets", "execs", "hours", "fabian", "puehringer", "tuukka", "kantola", "linear", "created", "manual", "registered", "accounts", "ordered", "number", "desc", "bugs", "user", "reported", "query", "issues", "any", "label", "case-sensitive", "matched", "connect", "bigquery", "something", "similar", "following", "settings", "select", "timestamp", "start", "cutoff", "end", "unnest", "struct", "string", "exec", "trunc", "hour", "instance", "status", "rudder", "schema", "finished", "inner", "join", "cross", "where", "between", "union", "summary", "count", "distinct", "instances", "group", "later", "build", "schedule" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 29, "matched_keywords": [ "check", "amount", "n8n", "reporting", "team", "channel", "hours", "linear", "manual", "accounts", "number", "desc", "issues", "any", "label", "connect", "similar", "settings", "select", "timestamp", "end", "struct", "hour", "instance", "join", "cross", "count", "group", "schedule" ] } }, { "prompt_file": "notification-router.json", "prompt": "Create a workflow that receives webhook notifications with a JSON body containing 'level' (high, medium, or low), 'title', and 'message'. Route them based on level: high priority goes to Microsoft Tea", "keywords": [ "receives", "webhook", "notifications", "json", "body", "containing", "level", "high", "medium", "low", "title", "route", "based", "priority", "goes", "microsoft", "teams", "team", "9b4c3a2f-1d8e-4f5b-a6c7-8e9f0b1d2c3a", "channel", "a1b2c3d4e5f6", "thread", "tacv2", "slack", "gmail", "alerts", "ourcompany", "notification", "include", "payload", "later", "build", "switch", "routing" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 13, "matched_keywords": [ "json", "body", "level", "high", "medium", "low", "based", "microsoft", "teams", "team", "channel", "gmail", "include" ] } }, { "prompt_file": "rest-api-data-pipeline.json", "prompt": "Fetch the latest posts from the JSONPlaceholder API (GET https://jsonplaceholder.typicode.com/posts). Filter out any posts where the title contains the word 'qui'. Then post a summary message to a Sla", "keywords": [ "latest", "posts", "jsonplaceholder", "typicode", "filter", "any", "where", "title", "contains", "word", "qui", "post", "summary", "slack", "channel", "called", "api-digest", "says", "many", "remain", "lists", "titles", "later", "build", "transformation", "schedule" ], "matched": true, "top_match": { "slug": "scrape-linkedin-job-listings-for-hiring-signals-prospecting--3580", "matches": 10, "matched_keywords": [ "posts", "filter", "any", "title", "word", "qui", "post", "lists", "titles", "build" ] } }, { "prompt_file": "set-edit-fields-contract.json", "prompt": "Every day, fetch one post from the JSONPlaceholder API (GET https://jsonplaceholder.typicode.com/posts/1). Then use an Edit Fields (Set) node, not a Code node, to add a field called caption from the p", "keywords": [ "day", "post", "jsonplaceholder", "typicode", "posts", "edit", "not", "code", "called", "caption", "title", "source", "while", "preserving", "original", "later", "build", "schedule", "transformation" ], "matched": true, "top_match": { "slug": "scrape-linkedin-job-listings-for-hiring-signals-prospecting--3580", "matches": 8, "matched_keywords": ["day", "post", "posts", "edit", "not", "code", "title", "build"] } }, { "prompt_file": "telegram-chatbot-memory-session.json", "prompt": "Build a Telegram chatbot workflow for a family assistant. It should receive Telegram messages, answer with an AI Agent using an OpenAI chat model, keep short-term conversation memory scoped separately", "keywords": [ "build", "telegram", "chatbot", "family", "assistant", "receive", "answer", "agent", "openai", "chat", "model", "keep", "short-term", "conversation", "memory", "scoped", "separately", "back", "same", "later", "expressions" ], "matched": true, "top_match": { "slug": "build-a-voice-ai-chatbot-with-elevenlabs-and-infranodus-know-4484", "matches": 13, "matched_keywords": [ "build", "telegram", "chatbot", "receive", "answer", "agent", "openai", "chat", "keep", "conversation", "memory", "back", "same" ] } }, { "prompt_file": "weather-alert.json", "prompt": "Every day at 8am, check the weather in Berlin using the OpenMeteo API and send me an email to david@thedavid.co.uk using the gmail node if it's going to rain", "keywords": [ "day", "8am", "check", "weather", "berlin", "openmeteo", "email", "david", "thedavid", "gmail", "going", "rain", "build", "schedule", "conditional" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 7, "matched_keywords": ["day", "check", "email", "gmail", "going", "rain", "schedule"] } }, { "prompt_file": "weather-monitoring.json", "prompt": "Every hour, check the current weather for London, New York, and Tokyo using the OpenWeatherMap API. Use 3 separate HTTP Request nodes, one per city. If any city has a temperature above 30°C, send a Te", "keywords": [ "hour", "check", "current", "weather", "london", "new", "york", "tokyo", "openweathermap", "separate", "per", "city", "any", "temperature", "above", "telegram", "alert", "chat", "-1001234567890", "listing", "hot", "cities", "log", "readings", "airtable", "table", "base", "appk2xgfgnoirl2gt", "tbl8xk3np5mq7rs9w", "columns", "humidity", "timestamp", "later", "build", "schedule", "conditional", "multi" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 14, "matched_keywords": [ "hour", "check", "current", "new", "per", "city", "any", "chat", "log", "table", "base", "timestamp", "schedule", "multi" ] } }, { "prompt_file": "workflow-data-table.json", "prompt": "I want you to build a workflow that will read n8n workflow databases and extract certain information and then populate that information in a data table called 'workflows'.\n\nThe schema of the data tabl", "keywords": [ "want", "you", "build", "read", "n8n", "databases", "extract", "certain", "information", "populate", "table", "called", "schema", "follows", "instanceid", "workflowid", "workflowname", "tags", "run", "multiple", "times", "update", "current", "rows", "rather", "than", "creating", "dupes", "instance", "wonderman", "users", "cloud", "later", "schedule" ], "matched": true, "top_match": { "slug": "extract-invoice-data-from-email-to-google-sheets-using-gpt-4-4376", "matches": 15, "matched_keywords": [ "you", "read", "n8n", "extract", "certain", "information", "populate", "table", "multiple", "times", "update", "current", "instance", "cloud", "schedule" ] } } ] }