An automated analysis tool for processing complex employee attendance records and generating professional docx and xlsx reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install analyzing-attendance-record-zhzh
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install analyzing-attendance-record-zhzh using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Zhuihui Branch Attendance Analyzer?
The Zhuihui Branch Attendance Analyzer is a specialized tool designed to handle the intricate attendance patterns of various bank branches. It processes raw Excel exports, applying sophisticated logic to account for different work schedules, weekend rotations, and departmental nuances. By integrating this into Openclaw Skills, developers can automate the labor-intensive process of auditing clock-in data.
This skill goes beyond simple counting; it performs deep data cleaning, such as filtering specific employees and reassigning personnel to correct sub-departments. It ensures that staff on weekend rotations are not unfairly penalized for weekday absences, providing a high degree of accuracy in reporting.
Zhuihui Branch Attendance Analyzer Use Cases
- Weekly generation of formal attendance reports in docx format for branch management.
- Calculation of departmental attendance rates to identify performance trends.
- Auditing missed clock-ins while accounting for compensatory leave and rotation systems.
- Generating detailed xlsx supplements for granular data verification.
How Zhuihui Branch Attendance Analyzer Works
- The skill ingests an xlsx file containing raw attendance data with specific group headers and columns.
- It performs a data quality check, removing excluded personnel and reclassifying staff into four specific sub-departments for the main office.
- The system identifies the work schedule for each branch, distinguishing between standard (Mon-Fri), weekend-rotation, and full-coverage (7-day) models.
- It calculates the expected clock-ins for each individual employee based on their actual weekend presence and weekday rest days.
- The tool aggregates the data to calculate the final attendance rate: (Actual Check-ins / Expected Check-ins) * 100%.
- It generates a formatted docx report and a detailed xlsx spreadsheet for the final output.
Zhuihui Branch Attendance Analyzer Setup
To deploy this tool within your Openclaw Skills environment, ensure you have the necessary dependencies for processing Excel and Word documents.
# Example setup for the environment
pip install python-docx pandas openpyxl
# Move the skill folder into your agent's skills directory
mv analyzing-attendance-record-zhzh/ your-agent/skills/
Zhuihui Branch Attendance Analyzer Data Schema & Taxonomy
The skill expects a specific Excel structure and produces two primary outputs:
| File Type | Purpose | Key Metadata |
|---|---|---|
| Input (xlsx) | Raw Attendance Data | Employee ID, Department, Clock-in/out times, Date (YYYYMMDD) |
| Output (docx) | Executive Summary | Attendance rates, missed clock-in lists, late/early leave details |
| Output (xlsx) | Detailed Supplement | Raw processed statistics per employee for audit trails |
Zhuihui Branch Attendance Analyzer Advanced Features
- Smart Rotation Logic: Automatically detects weekend-rotation staff by cross-referencing Saturday/Sunday records to adjust expected weekday counts.
- Departmental Mapping: Dynamically reassigns employees like 陈迪 to correct branches regardless of original data input.
- Holiday Integration: Supports external rule sets from
special-attendance-analysis-rules.mdto handle public holidays and performance-based constraints. - Multi-format Export: Synchronized generation of both human-readable reports and machine-readable supplements.
SKILL.md
Loading
Related Openclaw Skills
DeFi Scout
DeFi Scout delivers real-time on-chain financial intelligence, covering yields, prices, and protocol health across the Optimism and Base ecosystems.
Market Intelligence Claw
A real-time strategic intelligence layer that transforms live market data into actionable business insights for ecommerce and digital brands.
vLLM High-Performance Inference Engine
An expert assistant for deploying and optimizing large language models using the high-throughput vLLM inference engine.
Information Extraction
A professional-grade pipeline for extracting entities, relations, and events from raw text into normalized, graph-ready structured formats.
CrewAI
CrewAI is a sophisticated multi-agent orchestration framework designed to help developers build collaborative AI systems where specialized agents work together to solve complex tasks.
Book Highlights
A specialized AI agent skill designed to extract and format the most impactful highlights, quotes, and core insights from an extensive library of books.
Featured*
