Monthly Financial Reconciliation Goes from 3 Hours to 5 Minutes: TRAE Work's Skill Capability Solved This Overlooked "Minor Annoyance"

Not a finance professional, but every office worker will encounter one thing — organizing invoices.

I. A Real Pain Point: One Day Every Month When Nothing Else Gets Done

Let me ask a question first: Have you ever organized invoices?

If you've worked in finance, procurement, administration, or helped with company reimbursements, you should understand what I'm talking about.

At the end of every month, finance colleagues face a pile of PDF electronic invoices — sent by suppliers, generated by travel platforms, collected from various channels. They open them one by one, extract the invoice number, seller name, total price and tax, and total tax amount, then manually enter them into Excel.

It doesn't sound difficult, but the volume is overwhelming:

• Switching back and forth to copy and paste one invoice takes 1-2 minutes
• 200 invoices means 3-4 hours
• Eyes staring at numbers easily make mistakes; entering one wrong digit means a long search during reconciliation
• Some invoices have multiple line items that need to be entered one by one, which takes even more time

I'm not making this up. This is the real experience shared in the TRAE community by an IT staff member at a cosmetics brand. He said that every month, there's always one day when he can't do anything else but process and verify invoices.

Some might say: "Use OCR software" or "Use a PDF-to-Excel tool."

The reality is:

• PDF-to-Excel tools: The converted format is a complete mess, worse than manual entry
• Free OCR software: The recognition rate is frustratingly low
• General AI chat: Sending PDF invoices in batches always requires secondary processing of the returned results

The problem is small, but it genuinely impacts work efficiency.

Although I'm not in finance, I've been tormented by this same problem every month when helping my team organize reimbursement invoices. Until I discovered TRAE Work's Skill capability.

First, look at an intuitive data comparison:

📷 Invoice Organization Efficiency Comparison Chart

II. What is TRAE Work's Skill? Take 1 Minute to Understand

Before diving into the practical steps, it's necessary to explain what TRAE Work's Skill is.

TRAE Work is an AI office platform launched by ByteDance, offering dual Work and Code modes. Whether you are a developer, office worker, or student, you can use it to write proposals, do analysis, process files, and facilitate collaboration.

And Skill is a packaged, dedicated capability module within TRAE Work. You can think of it as an "AI's exclusive skill pack" — the complete operational workflow for a specific task is pre-packaged, so later you only need one sentence to invoke it, stably outputting results in the same format.

Simply put: Turn the complete workflow of repetitive tasks into a "skill," and from then on, execute it with one click each time, without rewriting prompts or repeatedly tuning the AI.

The TRAE Work Skill Marketplace already has many ready-made Skills, covering areas like development tools, efficiency improvement, data analysis, and content creation. Among them is a Skill specifically designed to solve the invoice organization problem — the ai-invoice-register (Invoice Organization) Skill.

Its capabilities include:

• Batch scanning PDF invoices in an entire folder
• Automatically identifying invoice number, seller name, total price and tax, and total tax amount
• Extracting line item details from each invoice (supports multi-page invoices)
• Automatically generating a formatted Excel file containing two worksheets: "Invoice Summary" and "Item Details"
• Each new task is independent, with no conflict or data contamination from historical tasks

📷 TRAE Work Skill Invocation Flow Diagram

III. Practical Process: From 3 Hours to 5 Minutes

Below is the entire process I used to handle month-end invoices with TRAE Work's Invoice Organization Skill.

Step 1: Dump All Invoice PDFs into One Folder

No need to organize or rename. Whether the PDF files are named with a string of numbers or Chinese descriptions, just dump them all in.

For example, the batch I needed to process this time was 187 electronic invoices sent by suppliers in August, all in PDF format, mixed in one folder.

📷 Screenshot of Invoice Folder

Step 2: Open TRAE Work, Switch to Work Mode

Open the TRAE Work desktop application, click the top-left corner of the interface, and switch to Work Mode — this is a mode specifically designed for non-development roles like product managers, operations, and data analysts.

Step 3: Invoke the Skill with One Sentence

Enter the following in the right-side dialog box:

Execute the ai-invoice-register Skill to organize all invoices in the folder into an Excel spreadsheet

Just this one sentence.

Then TRAE Work starts working automatically — opening PDFs one by one, parsing text, extracting fields, and writing to Excel.

The entire process shows real-time progress in the right-side task panel:

1. Scan folder, identify the number of PDF files
2. Parse PDFs one by one, extract key fields
3. Aggregate data, generate Excel spreadsheet
4. Verify data integrity

📷 TRAE Work Execution Progress Display

Step 4: Quick Verification, Fill in Gaps and Correct

After about 5 minutes, the Excel spreadsheet was generated.

Open it for a glance, filter to check for any empty rows, and manually fix a few individual extraction anomalies.

Out of 187 invoices, only 3 had some fields recognized abnormally due to scan quality issues, which were manually corrected. The remaining 184 were fully automated.

📷 Preview of Generated Excel Spreadsheet

IV. Deliverable Result: A Ready-to-Use Excel Register

TRAE Work ultimately delivered a standard Excel register containing two worksheets:

Sheet 1: Invoice Summary (as shown in the image above)

Sheet 2: Item Details

Invoice Number	Item Name	Quantity	Unit Price	Amount
24567890	Office Equipment Purchase	2	6,400.00	12,800.00
24567890	Accessories & Consumables	5	320.00	1,600.00
...	...	...	...	...

(Note: The detail sheet automatically breaks down multi-item invoices, listing them row by row)

Core Processing Logic (Code Example)

Although the Skill is packaged, understanding its processing logic makes it clearer what it does. Below is the core invoice parsing logic used internally by TRAE Work (Python pseudocode):

# Core Invoice Parsing Logic (Simplified Example)
import pandas as pd
import pdfplumber

def parse_invoice(pdf_path):
    """Parse a single PDF invoice, extract key fields"""
    with pdfplumber.open(pdf_path) as pdf:
        text = ''
        for page in pdf.pages:
            text += page.extract_text()
    
    # Use regular expressions to extract key fields
    import re
    invoice_no = re.search(r'Invoice Number[：:]\s*(\d+)', text)
    seller = re.search(r'Seller Name[：:]\s*([^\n]+)', text)
    total_amount = re.search(r'Total Price and Tax[：:]\s*[¥￥]?([\d,]+\.?\d*)', text)
    tax = re.search(r'Total Tax Amount[：:]\s*[¥￥]?([\d,]+\.?\d*)', text)
    date = re.search(r'Invoice Date[：:]\s*(\d{4}-\d{2}-\d{2})', text)
    
    # Extract line item details (multiple rows)
    items = []
    # ... parse detail rows
    
    return {
        'invoice_no': invoice_no.group(1) if invoice_no else '',
        'seller': seller.group(1).strip() if seller else '',
        'total': float(total_amount.group(1).replace(',', '')) if total_amount else 0,
        'tax': float(tax.group(1).replace(',', '')) if tax else 0,
        'date': date.group(1) if date else '',
        'items': items
    }

# Batch Processing
def batch_parse(folder_path):
    results = []
    for file in os.listdir(folder_path):
        if file.endswith('.pdf'):
            data = parse_invoice(os.path.join(folder_path, file))
            results.append(data)
    # Generate Excel
    df_main = pd.DataFrame([{k:v for k,v in r.items() if k!='items'} for r in results])
    # Break down details
    df_detail = []
    for r in results:
        for item in r['items']:
            df_detail.append({'Invoice Number': r['invoice_no'], **item})
    # Output
    with pd.ExcelWriter('Invoice_Register.xlsx') as writer:
        df_main.to_excel(writer, sheet_name='Invoice Summary', index=False)
        pd.DataFrame(df_detail).to_excel(writer, sheet_name='Item Details', index=False)

Efficiency Comparison

Method	Time Spent	Error Rate	Experience
Manual Entry	3-4 hours	High (easy to misread numbers)	Tedious, eye-straining
General AI Chat	1-2 hours (upload files one by one)	Medium	Repetitive operation, troublesome
TRAE Work Skill	5 minutes	Low	One sentence, wait for the result

187 invoices, automatically generated in 5 minutes, saving at least half a day compared to manual entry.

And this isn't a one-off — every month-end from now on, I just need to drop the new invoice PDFs into the folder, use the same one-sentence command, and it's done in 5 minutes.

V. Going Deeper: Migrating the Skill Mindset to Other Scenarios

Once you understand the logic of Skill, you'll find it's not just applicable to invoice organization.

The core idea is: encapsulate the complete workflow of repetitive tasks into a "skill," and invoke it with one click each time thereafter.

Scenario 1: Data Collection Automation

Someone encapsulated the complete operational process on a daily data platform into a TRAE Skill, containing a full automated pipeline:

Environment Check → Dependency Installation → Business Overview Collection → Conditional Filtering → Business Detail Data Collection → Data Cleaning → Data Merging → Data Validation → Output Final Excel

In TRAE Work, it only takes one sentence to start:

Execute the data-automation complete process

Then the AI will automatically read the Skill description, install dependencies, open a browser, complete login authorization, collect data one by one, clean and merge, and output Excel after validation passes.

Combined with TRAE Work's automated scheduled task feature, it can be configured to automatically execute every Monday at 7 AM. Every Monday when you arrive at your desk and turn on your computer, the latest data report is already there.

Scenario 2: Automatic Weekly Report Generation

A merchandise manager in the retail industry told TRAE Work the weekly report template and format requirements in advance, and every Friday, let it combine the week's work content to generate a complete weekly report according to the fixed template.

The weekly report has a fixed structure: what was completed this week, which projects progressed, which data changed, what problems were encountered, and how to handle them next week.

TRAE Work will organize according to this framework, and the generated content reads more like a genuine work review rather than a simple log.

What's saved is the time spent on "recalling and summarizing" — the most troublesome part of writing a weekly report on Friday isn't the writing itself, but re-checking chat records, spreadsheets, and everything done during the week.

Scenario 3: Data Analysis Reports

Merchandise management is inseparable from data. Previously, doing data analysis often meant opening spreadsheets, filtering, copying, pasting, summarizing, and then writing a paragraph that could be sent in the work group chat.

The current approach is: tell TRAE Work the analysis template, expression format, and business calibers in advance — which fields to look at, what logic to use for judgment, and what tone to output in the end. After providing sufficient context, send it the spreadsheet and let it output the analysis according to the template.

It can convert raw spreadsheets into language that can be directly communicated at work — which products are performing well, which need attention, which data is abnormal, which conclusions are worth discussing, it can organize a first draft.

Humans still need to judge, of course; AI cannot take responsibility for your business. But it can first process the materials to a state where "I can quickly make a judgment."

VI. Reusable Experience: You Can Directly Copy This Method

📋 General Operation Steps

1. Find Repetitive Tasks: Sort out which tasks in your work are "done every month/week, have a fixed process, are time-consuming but don't require much judgment"
2. Look for Existing Skills: First, check the TRAE Work Skill Marketplace (marketplace.trae.ai) to see if there's a ready-made Skill you can use directly
3. Or Package Your Own Skill: If there isn't one, tell TRAE Work the complete operational process and let it help you package it into a custom Skill
4. Invoke with One Sentence: From then on, you only need one sentence to start it each time
5. (Optional) Configure Scheduled Tasks: If it's a periodically executed task, configure automated scheduled tasks to achieve "unattended operation"

💡 Pitfall Avoidance Tips

1. Skill is More Stable Than General Chat: When there are too many files, general chat cannot verify if all were successfully transmitted; Skill is a packaged dedicated capability, more reliable than general chat
2. Format Must Be Uniform: Skill outputs results in a fixed format, consistent each time, no need for re-adjustment
3. Reusable Across Computers: A packaged Skill can be reused across computers and by multiple people, all stably outputting results in the same format
4. Run Through First, Then Automate: When using for the first time, manually invoke the Skill to run once, confirm the output format and content meet expectations, then configure scheduled tasks
5. Data Validation Cannot Be Skipped: After Skill execution, a quick check is necessary. Just like with invoice organization, a few files with poor scan quality might have recognition anomalies and need manual correction
6. PDF Quality Affects Recognition Rate: If invoices are scanned copies rather than electronic versions, the recognition rate will drop. It's recommended to use electronic PDF invoices whenever possible

🔧 Skill Creation Instruction Template

If you want to package your own Skill, you can refer to this template:

I want to create a new Skill for [describe task].

Input: Materials to upload (e.g., PDF folder, Excel spreadsheet, etc.)
Processing Steps:

1. [Step 1 description]
2. [Step 2 description]
   ...
   Output: [Output format and requirements]

Please help me generate the configuration file for this Skill.

TRAE Work will automatically generate the Skill based on your description, and afterward, you can invoke it just like you invoke ai-invoice-register.

VII. Some Extra Thoughts

This experience made me realize one thing: Many "minor annoyances" at work are not due to our lack of ability, but the lack of a tool to "encapsulate" repetitive work.

Invoice organization itself is not complicated — open PDF, copy fields, paste into Excel. But multiplied by 200, it becomes 3-4 hours of drudgery. The problem isn't "not knowing how," but "having to do it repeatedly every day/month."

TRAE Work's Skill solves exactly this problem — not replacing your thinking, but encapsulating repetitive "grunt work" into a one-click invocable skill.

What used to take 3 hours a month to organize invoices now takes 5 minutes. The time saved can be used for tasks that truly require judgment — verifying abnormal data, analyzing expenditure structures, optimizing procurement processes.

Time for work and life is sometimes chiseled out bit by bit like this.

And more importantly, once you understand the Skill mindset — encapsulating repetitive work into reusable skills — you'll find it can be migrated to countless scenarios: data collection, weekly report generation, data analysis, document processing...

Package once, benefit long-term.