Skip to main content

Ai-powered degree audit system with Google Sheets and GPT-5

Workflow preview

Workflow preview
100%
Ai-powered degree audit system with Google Sheets and GPT-5 preview
Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Run an AI powered degree audit for each senior student. This template reads student rows from Google Sheets, evaluates completed courses against hard coded program requirements , and writes back an...

Best for

  • Internal Wiki automation workflows
  • AI Chatbot automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.manualtrigger, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.googlesheets

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Ai-powered degree audit system with Google Sheets and GPT-5
Workflow name
Ai-powered degree audit system with Google Sheets and GPT-5

Run an AI-powered degree audit for each senior student. This template reads student rows from Google Sheets, evaluates completed courses against hard-coded program requirements, and writes back an AI Degree Summary of what's still missing (major core, Gen Eds, major electives, and upper-division credits). It's designed for quick advisor/registrar review and SIS prototypes.

Trigger: Manual — When clicking "Execute workflow"
Core nodes: Google Sheets, OpenAI Chat Model, (optional) Structured Output Parser
Programs included: Computer Science BS, Business Administration BBA, Psychology BA, Mechanical Engineering BS, Biology BS (Pre-Med), English Literature BA, Data Science BS, Nursing BSN, Economics BA, Graphic Design BFA

Who's it for

  • Registrars & advisors who need fast, consistent degree checks
  • Student success teams building prototype dashboards
  • SIS/EdTech builders exploring AI-assisted auditing

How it works

  1. Read seniors from Google Sheets (Senior_data) with: StudentID, Name, Program, Year, CompletedCourses.
  2. AI Agent compares CompletedCourses to built-in requirements (per program) and computes Missing items + a short Summary.
  3. Write back to the same sheet using "Append or update" by StudentID (updates AI Degree Summary; you can also map the raw Missing array to a column if desired).

Example JSON (for one student): { "StudentID": "S001", "Program": "Computer Science BS", "Missing": [ "GEN-REMAIN | General Education credits remaining | 6", "CS-EL-REM | CS Major Electives (200+ level) | 6", "UPPER-DIV | Additional Upper-Division (200+ level) credits needed | 18", "FREE-EL | Free Electives to reach 120 total credits | 54" ], "Summary": "All core CS courses are complete. Still need 6 Gen Ed credits, 6 CS electives, and 66 total credits overall, including 18 upper-division credits — prioritize 200/300-level CS electives." }

Setup (2 steps)

1) Connect Google Sheets (OAuth2)

In n8n → Credentials → New → Google Sheets (OAuth2) and sign in.

In the Google Sheets nodes, select your spreadsheet and the Senior_data tab.

Ensure your input sheet has at least: StudentID, Name, Program, Year, CompletedCourses.

2) Connect OpenAI (API Key)

In n8n → Credentials → New → OpenAI API, paste your key.

In the OpenAI Chat Model node, select that credential and a model (e.g., gpt-4o or gpt-5).

Requirements

  • Sheet columns: StudentID, Name, Program, Year, CompletedCourses
  • CompletedCourses format: pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101).
  • Program labels: should match the built-in list (e.g., Computer Science BS).
  • Credits/levels: Template assumes upper-division ≥ 200-level (adjust the prompt if your policy differs).

Customization

  • Change requirements: Edit the Agent's system message to update totals, core lists, elective credit rules, or level thresholds.
  • Store more output: Map Missing to a new column (e.g., AI Missing List) or write rows to a separate sheet for dashboards.
  • Distribute results: Email summaries to advisors/students (Gmail/Outlook), or generate PDFs for advising folders.
  • Add guardrails: Extend the prompt to enforce residency, capstone, minor/cognate constraints, or per-college Gen Ed variations.

Best practices (per n8n guidelines)

  • Sticky notes are mandatory: Include a yellow sticky note that contains this description and quick setup steps; add neutral sticky notes for per-step tips.
  • Rename nodes clearly: e.g., "Get Seniors," "Degree Audit Agent," "Update Summary."
  • No hardcoded secrets: Use credentials—not inline keys in HTTP or Code nodes.
  • Sanitize identifiers: Don't ship personal spreadsheet IDs or private links in the published version.
  • Use a Set node for config: Centralize user-tunable values (e.g., column names, tab names).

Troubleshooting

  • OpenAI 401/429: Verify API key/billing; slow concurrency if rate-limited.
  • Empty summaries: Check column names and that CompletedCourses uses |.
  • Program mismatch: Align Program labels to those in the prompt (exact naming recommended).
  • Sheets auth errors: Reconnect Google Sheets OAuth2 and re-select spreadsheet/tab.

Limitations

  • Not an official audit: It infers gaps from the listed completions; registrar rules can be more nuanced.
  • Catalog drift: Requirements are hard-coded in the prompt—update them each term/year.
  • Upper-division heuristic: Adjust the level threshold if your institution defines it differently.

Tags & category

Category: Education / Student Information Systems
Tags: degree-audit, registrar, google-sheets, openai, electives, upper-division, graduation-readiness

Changelog

v1.0.0 — Initial release: Senior_data in/out, 10 programs, AI Degree Summary output, append/update by StudentID.

Contact

Need help tailoring this to your catalog (e.g., per-college Gen Eds, capstones, minors, PDFs/email)?

📧 [email protected]
📧 [email protected]
🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/
🌐 ynteractive.com — https://ynteractive.com

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 clicking ‘Execute workflow’

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

Block 2 - Sticky Note68

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

Block 3 - OpenAI Chat Model1

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 4 - Structured Output Parser1

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 5 - Sticky Note69

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

Block 6 - Sticky Note57

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

Block 7 - Sticky Note5

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

Block 8 - Degree Audit Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.2

Block 9 - Add Student Degree Summary

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 10 - Get Student Data1

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

3. Summary Table

Workflow Ai-powered degree audit system with Google Sheets and GPT-5
Complexity intermediate
Nodes 10
Categories Internal Wiki, AI Chatbot
Author Robert Breen
Published 31 Aug 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/8093/8093.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 Ai-powered degree audit system with Google Sheets and GPT-5 do?

Run an AI powered degree audit for each senior student. This template reads student rows from Google Sheets, evaluates completed courses against hard coded program requirements , and writes back an...

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 Internal Wiki, AI Chatbot use case.