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Spot Workplace Discrimination Patterns with AI

38 nodes · manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart

Engine
n8n
Nodes
38
Trigger
scheduled/triggered
Source file
1666_Code_Manual_Automation_Webhook.json

Workflow flow

IntegrationsManualLmChatOpenAiHTTPHtmlInformationExtractorQuickChartChainLlm@n8n/n8n-nodes-langchain.lmChatOpenAiMergeSet@n8n/n8n-nodes-langchain.informationExtractorCode+1 more
100%
TRIGGER

When clicking ‘Test workflow’

Manual

OpenAI Chat Model1

@n8n/n8n-nodes-langchain.lmChatOpenAi

OpenAI Chat Model2

@n8n/n8n-nodes-langchain.lmChatOpenAi

OpenAI Chat Model

@n8n/n8n-nodes-langchain.lmChatOpenAi

SET company_name

Set

Define dictionary of demographic keys

Set

ScrapingBee Search Glassdoor

HTTP

Extract company url path

Html

ScrapingBee GET company page contents

HTTP

Extract reviews page url path

Html

ScrapingBee GET Glassdoor Reviews Content

HTTP

Extract Overall Review Summary

Html

Extract Demographics Module

Html

Extract overall ratings and distribution percentages

@n8n/n8n-nodes-langchain.informationExtractor

Extract demographic distributions

@n8n/n8n-nodes-langchain.informationExtractor

Define contributions to variance

Set

Set variance and std_dev

Set

Merge

Merge

Calculate Z-Scores and Effect Sizes

Set

Calculate P-Scores

Code

Format dataset for scatterplot

Code

Sort Effect Sizes

Set

Specify additional parameters for scatterplot

Set

Quickchart Scatterplot

HTTP

QuickChart Bar Chart

QuickChart

Text Analysis of Bias Data

@n8n/n8n-nodes-langchain.chainLlm

26 steps · flows top to bottom, branches left to right

Browse by integration

manuallmChatOpenAihttpRequesthtmlinformationExtractorquickChartchainLlm
Browse all integrations →
Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Spot Workplace Discrimination Patterns with AI is a free n8n workflow on OpenRuna — 38 nodes connecting manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm. Download the JSON, view the flow diagram, and import it into your n8n instance.

What this workflow does

"Spot Workplace Discrimination Patterns with AI" is an n8n automation built from 38 nodes spanning manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm. 38 nodes · manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart It starts from a scheduled/triggered trigger and routes data through every node in order. On OpenRuna you get the visual graph, the integration list, and a downloadable JSON ready to import into n8n. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Use it as a starting template when wiring manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm — adjust node parameters to your accounts and record IDs.
  • Import "Spot Workplace Discrimination Patterns with AI" into n8n, reconnect credentials for manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm, and run the same automation in your own workspace.
  • Share it with your team as a documented reference for scheduled/triggered automations in the manual stack.
  • Study how data moves from manual to lmChatOpenAi before building your own variant.

Example output

Imported into n8n, "Spot Workplace Discrimination Patterns with AI" exposes 38 configured nodes. Trigger type: scheduled/triggered. Integrations: manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm. Open each node after import to map credentials to your own manual and lmChatOpenAi accounts. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Paste the exported JSON for "Spot Workplace Discrimination Patterns with AI" into Claude and ask it to explain each of the 38 nodes. Claude is good at suggesting credential mappings for manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm, plus error-handling and idempotency improvements before you run it in production.

ChatGPT

Have ChatGPT generate a checklist for adapting "Spot Workplace Discrimination Patterns with AI" to your accounts — which manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm credentials to create and which node parameters to change first.

Cursor

Open the downloaded JSON in Cursor and use Agent mode to refactor hard-coded URLs into env vars, or to generate tests for any Code nodes. Keep the OpenRuna flow diagram open so you do not break connection order across the 38 nodes.

Frequently asked questions

How do I import "Spot Workplace Discrimination Patterns with AI" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Spot Workplace Discrimination Patterns with AI" use?
It uses: manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm. The flow diagram above shows how each service connects across the 38 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own manual and lmChatOpenAi credentials in n8n after import.
What trigger type does "Spot Workplace Discrimination Patterns with AI" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Spot Workplace Discrimination Patterns with AI" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for manual, lmChatOpenAi, httpRequest, html, informationExtractor, quickChart, chainLlm.

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