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Score and critique content drafts with OpenRouter and LangChain

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1. Workflow Overview

Quick Overview This subworkflow is called by a parent n8n pipeline to review a content draft against a provided brief using an OpenRouter chat model, returning structured scores, issues, and revisi...

Best for

  • Content Creation automation workflows
  • AI Summarization automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.executeworkflowtrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenrouter, n8n-nodes-base.code, n8n-nodes-base.stickynote

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Elvis Sarvia.

Original n8n.io source

1.1 Workflow description

Title
Score and critique content drafts with OpenRouter and LangChain
Workflow name
Score and critique content drafts with OpenRouter and LangChain

Quick Overview

This subworkflow is called by a parent n8n pipeline to review a content draft against a provided brief using an OpenRouter chat model, returning structured scores, issues, and revision notes the parent can use to decide whether to iterate or accept the draft.

How it works

  1. Receives the full pipeline state from a parent workflow execution, including the brief and current draft text.
  2. Sends the brief and draft to a LangChain Agent configured as an editorial “LLM-as-a-Judge” using an OpenRouter chat model.
  3. Produces a JSON review containing 1–10 scores for accuracy, tone, completeness, and clarity, plus an averaged overall score, issues list, and actionable revision notes.
  4. Parses the model output, falls back to a zero-score error review if parsing fails, and merges the review back into the original input object.
  5. Returns the enriched payload (original fields plus a review object) to the parent workflow for threshold-based decision-making.

Setup

  1. Add an OpenRouter API credential and select the model you want to use in the OpenRouter chat model node.
  2. Ensure the parent workflow passes the expected fields (at minimum brief and currentDraft) when calling this subworkflow.
  3. Save this workflow and reference it from the parent pipeline’s Execute Workflow step so it can be invoked after each writer iteration.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When Executed by Parent

Type / Role
n8n-nodes-base.executeWorkflowTrigger - executeWorkflowTrigger
Config choices
Version 1.1

Block 2 - Reviewer Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 1.7

Block 3 - OpenRouter - Reviewer

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices
Version 1

Block 4 - Parse Review Output

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 5 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

3. Summary Table

Workflow Score and critique content drafts with OpenRouter and LangChain
Complexity intermediate
Nodes 5
Categories Content Creation, AI Summarization
Author Elvis Sarvia
Published 26 May 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/15951/15951.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Score and critique content drafts with OpenRouter and LangChain do?

Quick Overview This subworkflow is called by a parent n8n pipeline to review a content draft against a provided brief using an OpenRouter chat model, returning structured scores, issues, and revisi...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Content Creation, AI Summarization use case.