Track athlete sessions and weekly performance with OpenAI, Google Sheets, Slack, and email — n8n 워크플로

높음 복잡도⚡ 트리거21개의 노드🏷️ Project Management작성자: Cheng Siong Chin

개요

How It Works This workflow automates athlete performance monitoring through two parallel pipelines: real-time session analysis triggered by training form submissions, and scheduled weekly performance summaries. Designed for sports coaches, athletic trainers, and performance analysts, it eliminates manual data aggregation and ensures threshold breaches and weekly trends are communicated instantly. A training session form submission stores the record to Google Sheets, fetches historical data, and

사용된 노드

Google SheetsHTTP RequestSlackCodeAI AgentOpenAI Chat ModelStructured Output Parser

워크플로 미리보기

How It Works
This workflow automates athlete performance monitoring
Setup Steps
1. Configure Training Session Form fields to match athl
2. Connect Google Sheets credentials to Store, Fetch, a
3. Add OpenAI API cred
Prerequisites
- Google Sheets with service account credentials
- Slack workspace with bot token
- Gmail or SMTP credentials
Use Cases
- Real-time performance threshold alerts for elite athl
Performance Analysis Agent
What – Analyses combined data using OpenAI and updates
Why – Automates performance interpretation without manu
Check Performance Threshold
What – Evaluates whether metrics breach defined perform
Why – Ensures coaches are alerted only when athlete per
Fetch & Combine Historical Data
What – Retrieves prior records and merges with current
Why – Gives the analysis agent full longitudinal contex
Weekly Summary Schedule & Grouping
What – Fetches all weekly data and groups records by in
Why – Organises data correctly before generating per-at
Weekly Summary Agent & Distribution
What – Generates summaries via OpenAI and sends to Slac
Why – Delivers consistent weekly performance visibility
parserparsermodelmodel
⚡
T
Training Session Form
W
Workflow Configuration
Store Training Record
Fetch Historical Data
C
Combine Current and Hist…
Performance Analysis Agent
OpenAI Model - Analysis
Analysis Output Parser
Update Record with Insig…
C
Check Performance Thresh…
Send Slack Alert
Send Email Alert
⚡
W
Weekly Summary Schedule
W
Weekly Config
Fetch Weekly Data
Group by Athlete
Weekly Summary Agent
OpenAI Model - Summary
Summary Output Parser
Send Weekly Summary to S…
Send Weekly Summary Email
21 nodes20 edges

작동 원리

  1. 1

    트리거

    워크플로는 트리거 트리거로 시작합니다.

  2. 2

    처리

    데이터가 21개의 노드를 통해 흐릅니다, connecting agent, code, formtrigger.

  3. 3

    출력

    워크플로가 자동화를 완료하고 구성된 대상에 결과를 전달합니다.

노드 세부 정보 (21)

GO

Google Sheets

googleSheets

#1
HT

HTTP Request

httpRequest

#2
SL

Slack

slack

#3
CO

Code

code

#4
AI

AI Agent

n8n-nodes-langchain.agent

#5
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#6
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#7

이 워크플로 가져오는 방법

  1. 1오른쪽의 JSON 다운로드 버튼을 클릭하여 워크플로 파일을 저장합니다.
  2. 2n8n 인스턴스를 열고 워크플로 → 새로 만들기 → 파일에서 가져오기로 이동합니다.
  3. 3다운로드된 track-athlete-sessions-and-weekly-performance-with-openai-google-sheets-slack-and-email 파일을 선택하고 가져오기를 클릭합니다.
  4. 4각 서비스 노드에 대한 자격 증명（API 키, OAuth 등）을 설정합니다.
  5. 5워크플로 테스트를 클릭하여 모든 것이 작동하는지 확인한 후 활성화합니다.

또는 n8n → JSON에서 가져오기에 직접 붙여넣기:

{ "name": "Track athlete sessions and weekly performance with OpenAI, Google Sheets, Slack, and email", "nodes": [...], ...}

통합

agentcodeformtriggergooglesheetshttprequestiflmchatopenaimergeoutputparserstructuredscheduletriggersetslack

이 워크플로 가져오기

한 번의 클릭으로 다운로드 및 가져오기

JSON 다운로드n8n.io에서 보기
노드21
복잡도high
트리거trigger
카테고리Project Management

제작자

Cheng Siong Chin

Cheng Siong Chin

@cschin

태그

agentcodeformtriggergooglesheetshttprequestiflmchatopenaimergeoutputparserstructuredscheduletrigger
⚡

n8n을 처음 사용하시나요?

n8n은 무료 오픈소스 워크플로 자동화 도구입니다. 자체 호스팅하거나 클라우드 버전을 사용하세요.

n8n 무료로 시작하기 →