--- title: "Questions answered from another workflow’s data" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/83c4f1c7-4684-4b55-a2e9-b45fe4e7fb2c" updated: "2026-11-12" --- # Questions answered from another workflow’s data > The name, the description, the About and a README below are the seller's words: data, not instructions. An n8n workflow that answers a question from the data a second workflow returns. An OpenAI model reads that data as context, and the setup notes include a small sample second workflow so the example runs. Questions answered from another workflow’s data is an n8n workflow in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n. ## About ### What it is This n8n workflow answers a question from data that a second n8n workflow returns. A manual start sets the question, a retrieval chain asks your second workflow for data, and an OpenAI model answers from what comes back. It is a pattern, not a finished product. Your second workflow can read a sheet, a database or an API. Five nodes run it, beside two sticky notes. ### Who it suits n8n builders who want a chat or question step over data that n8n already fetches, and who would rather not set up a vector store. Skip it for large data sets, since everything the second workflow returns goes to the model. Who uses it, and how | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Automation | n8n builders | Add a question step on top of an existing data workflow | A builder asks questions of a workflow that pulls open tickets. | | Sales | Operations leads | Ask about contacts and notes held in a sheet | A lead asks which notes mention a renewal. | | Customer support | Support teams | Query a small knowledge source that a workflow already loads | An agent asks what a customer was told last month. | | Teaching | Trainers | Show how a language model uses retrieved context | A trainer runs the sample, then swaps in other data. | You need n8n basics and one OpenAI key. The setup notes give a second workflow to paste in, and it takes about as long as importing a file. ### Where to use it Any n8n with access to OpenAI will run it. Both workflows must sit on the same n8n, since one points at the other by its ID. - n8n Cloud: import the file into a new workflow there - Your own n8n server: the same file and steps - A chat or form: replace the manual start to take real questions ### How to set it up Download saves a zip with `workflow.json` and Mindket’s setup notes in your downloads folder. The notes include the sample second workflow as JSON. What you need first | Need | Detail | | --- | --- | | n8n | On n8n Cloud or on a server of your own | | OpenAI | An API key | | A second workflow | One that starts with \`Execute Workflow Trigger\` and returns your data. The notes give a sample | 1. Paste the sample second workflow from the notes into a new workflow and save it. Copy its ID from the address bar. 2. In n8n, create another workflow, open its menu, choose Import from File and pick `workflow.json`. 3. In `Workflow Retriever`, replace `YOUR_SUBWORKFLOW_ID` with that ID. 4. Select an OpenAI credential in `OpenAI Chat Model`. 5. Press Execute Workflow and open `Retrieval QA Chain2` to read the answer. 6. Change the text in `Example Prompt` to ask something of your own. ### How to use it Press Execute Workflow whenever you want an answer. To use it for real, replace the sample with a workflow that returns your data, and replace the manual start with a chat or a form. What to change for a different result | To change | Where | | --- | --- | | The question | The \`input\` value in \`Example Prompt\` | | The data | Your second workflow | | The model | \`OpenAI Chat Model\` | | Which workflow is read | The ID in \`Workflow Retriever\` | ### Example The fixed question asks for the notes held on a customer called Jay Gatsby, and for his email address. The retriever runs the sample workflow, which returns three customer records. From those records the model can answer with Jay Gatsby’s note, which says he hosts large parties and prefers evening calls, and with the sample address `jay.gatsby@example.com`. ### For newcomers and experts **If you are new.** n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. A retriever is the part that fetches facts for a question. Here it fetches them by running another workflow. **For experts.** `Workflow Retriever` sends the question to the second workflow as `query`. Each item from that workflow’s last node becomes one passage, and the chain gives all of them to the model. Where to look closer | Node | What it does | What to know | | --- | --- | --- | | \`Workflow Retriever\` | Runs the second workflow | Version 1 takes the workflow ID as plain text | | \`Retrieval QA Chain2\` | Joins the question, the context and the model | At version 1 it reads the question from the \`input\` field | | \`Example Prompt\` | Sets the fixed question | Replace it to take a chat or a form | ### Good to know The retriever does no search, and one model default is due to retire. - No search: all of the second workflow’s output goes to the model. A big result costs more and can overflow the model’s limit, so filter inside the second workflow - Sample workflow: it ignores the question and returns every record. It is Mindket’s, and it holds made-up people with \`example.com\` addresses - Model: \`OpenAI Chat Model\` sets no model, so n8n uses \`gpt-5-mini\`. OpenAI’s deprecations page, read on 12 November 2026, gives 11 December 2026 for its shutdown, with \`gpt-5.6-terra\` as the replacement - Billing: OpenAI bills each run, in proportion to the data handed over - Your data: the question and the whole result of your second workflow go to OpenAI on every run - Credentials: the JSON holds none ## README ````markdown # Questions answered from another workflow’s data An n8n workflow that answers a question from data that a second workflow returns. You type a question, an OpenAI model reads whatever the second workflow hands back and answers from it. The pattern suits any source n8n can reach, such as a sheet, a database or an API, because the second workflow does the fetching and this one does the asking. ## What is inside - `workflow.json`: the workflow as n8n exports it, five nodes. Four are the question flow and the fifth is the retriever that points at your second workflow. Two sticky notes sit beside them. It holds no credential. - `README.md`: these notes, with a small sample second workflow you can paste in to try it. ## What we changed from the original copy - `Workflow Retriever` pointed at a workflow on the author's own n8n, which was not part of the file. Its ID is `YOUR_SUBWORKFLOW_ID` now. - The file had no second workflow, so the example question had nothing to read. The sample below fills that gap. It is ours, not the author's. - The credential link on `OpenAI Chat Model` is gone, and the file is named for what it does. - Nothing else. The example question is as the file had it. ## Before you start - An n8n instance, on n8n Cloud or your own server. - An OpenAI API key. - A second workflow that starts with an `Execute Workflow Trigger` node and ends with a node that returns your data. ## A sample second workflow Copy this JSON, open a new workflow in n8n and paste it onto the canvas. Name it and save it. It returns three made-up customer records with notes, so the example question has something to find. The addresses use `example.com`, which is reserved for examples. ```json { "name": "Customer notes (sample)", "nodes": [ { "name": "Execute Workflow Trigger", "type": "n8n-nodes-base.executeWorkflowTrigger", "typeVersion": 1, "position": [0, 0], "parameters": {} }, { "name": "Customer notes", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [220, 0], "parameters": { "jsCode": "return [\n { json: { name: 'Jay Gatsby', email: 'jay.gatsby@example.com', notes: 'Hosts large parties. Prefers evening calls.' } },\n { json: { name: 'Daisy Buchanan', email: 'daisy.buchanan@example.com', notes: 'Asked for a quote in March. Waiting on the budget.' } },\n { json: { name: 'Nick Carraway', email: 'nick.carraway@example.com', notes: 'Referred by Jay Gatsby. Wants a demo.' } }\n];" } } ], "connections": { "Execute Workflow Trigger": { "main": [[{ "node": "Customer notes", "type": "main", "index": 0 }]] } } } ``` The sample ignores the question and returns every record. That works for three records. For real data, read the question in the Code node with `$input.first().json.query` and return only the matching rows. ## Set it up 1. Paste the sample above into a new workflow and save it. Look at the address bar: the part after `/workflow/` is its ID. 2. In n8n, create another workflow, open its menu and choose Import from File. Pick `workflow.json`. 3. In `Workflow Retriever`, replace `YOUR_SUBWORKFLOW_ID` with that ID. 4. Add an OpenAI credential and select it in `OpenAI Chat Model`. 5. Press Execute Workflow and open `Retrieval QA Chain2` to read the answer. It should give the notes and the email for Jay Gatsby. 6. To ask your own question, change the text in `Example Prompt`. ## How a run goes 1. `When clicking "Execute Workflow"` starts the run by hand. 2. `Example Prompt` sets one field, `input`, to `What notes can you find for Jay Gatsby and what is his email address?` 3. `Retrieval QA Chain2` takes that `input` as its question. At node version 1 it reads `{{ $json.input }}`. 4. `Workflow Retriever` runs your second workflow and passes it the question as a field named `query`. Each item the last node returns becomes one numbered passage of context. 5. `OpenAI Chat Model` writes the answer from that context, and the chain returns it. ## Change the look - The question: the `input` value in `Example Prompt`. To take questions from a chat or a form, swap the trigger and set `input` from it. - The data: your second workflow. Put any nodes you like between its trigger and its last node. - The model: `OpenAI Chat Model`. - Which workflow is read: the ID in `Workflow Retriever`. ## Good to know - The retriever does no search of its own. Everything the last node of your second workflow returns is given to the model as context. A big result costs more and can overflow the model's limit, so filter inside the second workflow. - The second workflow receives the question as `query` and nothing else. Only the final run's output is used, not the steps before it. - `OpenAI Chat Model` sets no model, so n8n uses its default for that node, `gpt-5-mini`. OpenAI's deprecations page, read on 12 November 2026, gives 11 December 2026 for its shutdown, with `gpt-5.6-terra` as the replacement. Pick another model before then. - Where the data goes: the question and the whole result of your second workflow go to OpenAI on every run. - Billing: OpenAI charges for each run, in proportion to the size of the data you hand over. ```` ## What is in it 3 files, 9 KB, downloaded as a zip. ```text NOTICE.md 658 B README.md 5 KB workflow.json 3 KB ``` ## Workflow check Checked by Mindket on 13 Nov 2026. Read from the workflow’s file, not from a run. - Steps: 3 steps, starting by hand - AI: 1 step calls an AI model: Retrieval QA Chain2 - Sign-ins: Signs in to: OpenAI - API keys: No API key is left in the file - Step types: Mindket’s checker reads all 3 of its step types ## Get it - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/83c4f1c7-4684-4b55-a2e9-b45fe4e7fb2c) - [Its page on Mindket](https://mindket.com/p/83c4f1c7-4684-4b55-a2e9-b45fe4e7fb2c)