Task Time Analysis: Automated Overspend Time Insights for ClickUp and More — n8n 工作流

高 复杂度⚡ 触发器33 个节点🏷️ Project Management作者：Krupal Patel

概览

This workflow automatically analyses tasks to uncover why the actual time spent exceeds the original estimates. It connects with ClickUp(Can do with any PMS like JIRA, Asana, Monday and more) and other project management tools to generate clear insights on overspending trends. Save time, improve planning accuracy, and boost team productivity with automated task time analysis with two types of reports.

“Why needed extra time?”** – Reasons users requested extensions or faced blockers.

“Why went

使用的节点

HTTP RequestClickUpCodeAI AgentOpenAI Chat ModelSimple Memory

工作流预览

Why requested for extra time?
Checklist Name = Why needed Extra time?
List of reasons with the comment link if possible.
Why goes over estimation.
Checklist Name = Why goes over estimation?
Evaluate comments and discussions and based on that pre
Fetch Overtime Tasks
Pull ClickUp tasks in target statuses and folders with
Get Time Entries
Fetch time entries for each task to analyze where time
Get Comments and Its threads
Pull all user comments and thread replies from ClickUp.
AI-Generated Checklist
Send task data to GPT to extract two reason lists (extr
Time spent on
1) Development
2) Scoping
3) Commenting+Call+Documentation
4) PR Review
5) QA
memorymemorymodelmodel
⚡
W
When clicking ‘Test work…
OpenAI Chat Model
Simple Memory
C
Convert to File
Get Clickup Tasks
Fetch Time entries via t…
Filter out unnecessary d…
I
If task has crossed esti…
Fetch Master comments
L
Loop Over Master comments
I
If comments got thread c…
Fetch comment threads
M
Merge thread comments wi…
R
Re-merge all master comm…
Re-structure comments to…
M
Merge task data, comment…
Modify Task data
M
Move to next master comm…
Modify Master comment data
Return Comments data
Modify threads comment d…
Sort Master comments old…
Modify Time entries data
Code
Destructure & Filter com…
OpenAI Chat Model1
Simple Memory1
Generate time insights
Generate Reason checklist
Code2
M
Merge
Code3
Generate Prompt with Tim…
33 nodes38 edges

工作原理

  1. 1

    触发器

    工作流由 触发器 触发器启动。

  2. 2

    处理

    数据流经 33 个节点, connecting agent, clickup, code。

  3. 3

    输出

    工作流完成自动化并将结果发送到配置的目标。

节点详情 (33)

HT

HTTP Request

httpRequest

#1
CL

ClickUp

clickUp

#2
CO

Code

code

#3
AI

AI Agent

n8n-nodes-langchain.agent

#4
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#5
SI

Simple Memory

n8n-nodes-langchain.memoryBufferWindow

#6

如何导入此工作流

  1. 1点击右侧 下载 JSON 按钮保存工作流文件。
  2. 2打开你的 n8n 实例，依次点击 工作流 → 新建 → 从文件导入。
  3. 3选择下载的 task-time-analysis-automated-overspend-time-insights-for-clickup-and-more 文件并点击导入。
  4. 4为每个服务节点配置 凭证（API 密钥、OAuth 等）。
  5. 5点击 测试工作流 验证一切正常，然后激活它。

或直接在 n8n → 从 JSON 导入 中粘贴：

{ "name": "Task Time Analysis: Automated Overspend Time Insights for ClickUp and More", "nodes": [...], ...}

集成

agentclickupcodeconverttofilehttprequestiflmchatopenaimanualtriggermemorybufferwindowmergesplitinbatches

获取此工作流

一键下载并导入

下载 JSON在 n8n.io 上查看
节点33
复杂度high
触发器trigger
分类Project Management

创建者

Krupal Patel

Krupal Patel

@krupalpatel

标签

agentclickupcodeconverttofilehttprequestiflmchatopenaimanualtriggermemorybufferwindowmerge
⚡

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