Ticket Stats

企业内部咨询工单统计分析。用于处理Excel格式的工单数据，统计每日接收工单数量、处理完成数量、未及时回复数量，并根据关键词自动归类到功能模块（订单交易、经营数据、门店设置、账号管理、商品管理、营销活动、顾客评价），生成带可视化图表的每日摘要报告。

Security Scan

The skill's code and SKILL.md are consistent with its stated purpose (analyzing Excel ticket data and producing charts); it asks for no credentials, performs no network activity, and has no install-time downloads.

Purpose & Capability

Name/description (ticket statistics and classification) align with the included script and SKILL.md. The script reads Excel/CSV, classifies by keywords, computes metrics, and generates charts — all expected for this purpose.

Instruction Scope

Runtime instructions limit actions to reading a provided Excel/CSV file, local processing with pandas, and optional local chart output. There are no instructions to read unrelated system files, environment variables, or to send data externally.

Install Mechanism

Instruction-only skill with a Python script; no install spec or remote downloads. It relies on standard Python packages (pandas, openpyxl, matplotlib) which the user must install — no high-risk install URLs or archive extraction present.

Credentials

The skill does not request any environment variables, credentials, or config paths. The resources it needs (local Excel/CSV files and optional Python libs) are proportionate to its function.

Persistence & Privilege

always is false and the skill does not modify agent/system configurations. It runs only when invoked and does not request elevated or persistent privileges.

Assessment

This appears coherent and limited in scope, but take normal precautions: run the script in an isolated environment (virtualenv/container), review the script yourself if you can, and ensure the input files do not contain secrets you don't want written to disk. Install required Python packages (pandas, openpyxl, matplotlib) from official sources before use. The script writes chart image files to the working directory and does not perform network I/O or request credentials.

工单统计分析 Skill

数据要求

Excel表格需包含以下列：

• 工单编号 - 唯一标识
• 提交时间 - 工单创建时间
• 状态 - 待处理/处理中/已解决
• 问题描述 - 工单内容文本
• 回复时间 - 首次回复时间（可选，用于计算响应时长）

功能模块关键词

模块	关键词
订单交易	订单、支付、退款、下单、交易、订单查询
经营数据	报表、销售额、营收、流水、统计、经营分析
门店设置	门店、店铺、营业时间、地址、门店配置
账号管理	账号、登录、密码、权限、角色、用户
商品管理	商品、上架、下架、库存、SKU、商品信息
营销活动	优惠券、活动、折扣、满减、推广
顾客评价	评价、评分、评论、星级、反馈

使用方式

# 1. 读取Excel工单数据
import pandas as pd
df = pd.read_excel("工单数据.xlsx")

# 2. 统计各项指标
# - 接收工单数：当日新建工单
# - 已解决数：状态为"已解决"的工单
# - 未及时回复：回复时间-提交时间 > 1小时

# 3. 根据关键词自动归类
def classify_ticket(description):
    keywords = {...}  # 见上方表格
    for module, words in keywords.items():
        if any(w in description for w in words):
            return module
    return "其他"

# 4. 生成报告和可视化
# - 使用 matplotlib/plotly 生成图表
# - 输出为图片或HTML

输出格式

每日摘要包含：

1. 核心指标卡片（接收、处理完成、未及时回复）
2. 各模块工单分布饼图
3. 按时段/日期的工单趋势图
4. 问题关键词云或词频统计

脚本位置

使用 scripts/analyze_tickets.py 进行分析：

python scripts/analyze_tickets.py <工单Excel文件路径> [--date YYYY-MM-DD]