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Bidding Analysis Report
by
Austin0208
· GitHub ↗
· v1.0.0
· MIT-0
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Install in OpenClaw
/install bidding-analysis-report
Description
招标数据分析报告生成技能 - 支持AI项目占比分析、年度趋势分析、TOP机构排名,自动生成Word/PDF报告,嵌入高质量图表。适用于高校招标、政府采购、企业采购等场景。
README (SKILL.md)
招标数据分析报告生成技能
功能概述
本技能用于分析招标数据并生成专业报告,支持:
- AI项目占比分析 - 计算AI相关招标项目数和金额占比
- 年度趋势分析 - 分析多年度项目数和金额变化趋势
- TOP机构排名 - 统计招标项目数/金额排名前N的机构
- 分机构详细分析 - 每个机构的年度趋势和拓展建议
- 图表自动生成 - 嵌套环形图、百分比柱状图
- 报告输出 - Word格式(推荐)或PDF格式
使用场景
- 高校招标数据分析
- 政府采购AI项目统计
- 企业采购趋势分析
- 行业招标报告生成
输入要求
数据格式
Excel文件(.xlsx),需包含以下字段:
项目名称- 招标项目名称项目主体- 项目分类/类型成交金额(元)- 中标金额信息采集日期- 招标日期(时间戳或日期格式)甲方名称- 招标机构名称
AI项目识别
默认关键词:人工智能、AI、智能、大数据、机器学习、深度学习、智慧
输出格式
Word报告(推荐)
- 字体:微软雅黑(或系统支持的 Droid Sans Fallback)
- 行距:1.5倍行距
- 图表:嵌入PNG图片,居中显示
- 关键数据:加粗显示
图表类型
- 嵌套环形图 - 外环项目数占比,内环金额占比
- 百分比柱状图 - 年度趋势对比
配色方案(明亮科技风)
- AI项目数:亮橙色
#FF8C42 - AI金额:青色
#00F5D4 - 其他项目:亮蓝色
#7ED4FF - 其他金额:蓝色
#00D4FF
使用方法
基本用法
from bidding_analysis_report import BiddingReport
# 创建报告实例
report = BiddingReport(
data_path='招标数据.xlsx',
ai_keywords=['人工智能', 'AI', '智能', '大数据'],
output_format='word' # 或 'pdf'
)
# 生成报告
report.generate(
title='昆明高校近三年AI项目分析报告',
top_n=10, # TOP机构数量
detail_n=5 # 详细分析的机构数量
)
命令行用法
python bidding_report.py \
--data 招标数据.xlsx \
--title "昆明高校AI招标分析报告" \
--output report.docx \
--top 10 \
--detail 5
报告结构
一、总体情况
- AI项目数占比、金额占比(嵌套环形图)
- 年度发展趋势分析(百分比柱状图)
二、TOP机构
- 项目数占比最高的N个机构列表
- 包含:机构名称、总招标数、招标总金额、AI项目数、AI金额
- 结合机构特点分析AI项目关联
三、分机构详细情况
每个机构包含:
- 近3年招标项目总数及金额、AI项目数及金额(嵌套环形图)
- 分年度AI项目趋势分析(百分比柱状图)
- 拓展建议
技术实现
依赖库
pandas>=1.3.0
matplotlib>=3.5.0
python-docx>=0.8.11
openpyxl>=3.0.0
中文字体配置
import matplotlib.pyplot as plt
# 优先使用微软雅黑,回退到系统支持字体
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei', 'Droid Sans Fallback', 'SimHei']
plt.rcParams['axes.unicode_minus'] = False
图表生成
# 嵌套环形图
fig, ax = plt.subplots(figsize=(12, 8))
wedges1 = ax.pie(outer_vals, radius=1.3, colors=colors_outer,
wedgeprops=dict(width=0.35, edgecolor='white'))
wedges2 = ax.pie(inner_vals, radius=0.95, colors=colors_inner,
wedgeprops=dict(width=0.35, edgecolor='white'))
# 保存为PNG
plt.savefig('chart.png', dpi=150, bbox_inches='tight', facecolor='white')
Word文档生成
from docx import Document
from docx.shared import Inches, Pt
doc = Document()
# 设置字体和行距
style = doc.styles['Normal']
style.font.name = 'Microsoft YaHei'
style.font.size = Pt(12)
# 插入图表
doc.add_picture('chart.png', width=Inches(5.5))
# 数据加粗显示
p = doc.add_paragraph()
p.add_run('总项目数:')
run = p.add_run('6,786')
run.bold = True
配置选项
| 参数 | 说明 | 默认值 |
|---|---|---|
data_path |
数据文件路径 | 必填 |
ai_keywords |
AI项目识别关键词 | ['人工智能','AI','智能',...] |
output_format |
输出格式 | 'word' |
top_n |
TOP机构数量 | 10 |
detail_n |
详细分析机构数量 | 5 |
chart_dpi |
图表分辨率 | 150 |
line_spacing |
行距倍数 | 1.5 |
注意事项
- 中文字体:优先使用微软雅黑,系统不支持时自动回退到 Droid Sans Fallback
- 数据格式:确保Excel文件包含必需字段,日期字段需可解析
- 图表嵌入:Word格式推荐,PDF格式中文字体支持有限
- 数据填充:使用
.format()或字符串拼接,避免 f-string 编码问题
示例输出
昆明高校AI招标分析报告(2023-2026)
总体情况:
- 总招标项目:6,786项
- AI相关项目:1,193项(占比 17.6%)
- 总招标金额:96亿元
- AI项目金额:15亿元(占比 15.6%)
年度趋势:
- 2023年:AI项目占比 14.8%
- 2024年:AI项目占比 16.8%
- 2025年:AI项目占比 20.7%
- 2026Q1:AI项目占比 15.7%
TOP10高校:
- 云南大学 - AI项目61项
- 昆明理工大学 - AI项目54项
- 云南开放大学 - AI项目33项 ...
更新日志
v1.0.0 (2026-04-21)
- 初始版本发布
- 支持AI项目占比分析
- 支持年度趋势分析
- 支持TOP机构排名
- 支持Word/PDF报告输出
- 嵌套环形图和百分比柱状图
- 明亮科技风配色方案
作者: OpenClaw Team
许可: MIT License
Usage Guidance
This skill appears to do what it claims: analyze an Excel (.xlsx) bidding dataset and produce charts and a Word report. Before installing or running it: (1) review and test it on non-sensitive sample data because it reads and writes files locally; (2) run in a virtualenv or isolated environment and install requirements via pip to limit dependency risk; (3) note minor implementation issues — date parsing uses unit='ms' which may fail for non-timestamp date formats, the code expects a '序号' column when producing TOP orgs, and division-by-zero may occur if total_amount is zero; (4) PDF output is advertised but not clearly implemented in the provided code — expect Word (docx) output by default; (5) inspect the code yourself if you handle sensitive procurement data to ensure logging/outputs meet your privacy requirements.
Capability Analysis
Type: OpenClaw Skill
Name: bidding-analysis-report
Version: 1.0.0
The skill bundle is a legitimate tool for analyzing bidding data and generating Word reports. The core logic in `bidding_report.py` uses standard data science libraries (pandas, matplotlib) and the python-docx library to process Excel files and create formatted documents with embedded charts. No evidence of data exfiltration, unauthorized network access, or malicious instructions was found in the code or the SKILL.md documentation.
Capability Assessment
Purpose & Capability
The name/description (招标数据分析报告生成) align with the code and SKILL.md: reading Excel, analyzing AI-related projects, generating charts, and producing Word reports. Required libraries (pandas, matplotlib, python-docx, openpyxl, numpy) match the stated functionality. One minor mismatch: the docs advertise Word/PDF output but the visible code primarily implements Word report generation; explicit PDF export/conversion is not shown in the provided code (possible omission or unimplemented feature).
Instruction Scope
SKILL.md and README instruct running the script against a local .xlsx file and creating local PNG/DOCX outputs. The runtime instructions and code only read the provided Excel, write chart PNGs and a Word file, and do not reference unrelated system paths, other credentials, or remote endpoints. No steps instruct the agent to gather unrelated system context or exfiltrate data.
Install Mechanism
No install spec in the registry; dependencies are standard Python packages listed in requirements.txt and the README recommends pip install -r requirements.txt. There are no downloads from unknown URLs, no archive extraction, and no brew/npm installs. This is low risk from an install-mechanism perspective.
Credentials
The skill requests no environment variables, credentials, or config paths. It operates on user-supplied Excel files and writes local outputs only. There are no disproportionate or unrelated secret requests.
Persistence & Privilege
The skill does not request always:true and does not modify other skills or system-wide settings. It writes output files (charts, docx) to the working directory as expected for a reporting tool. Autonomous invocation is allowed by default (disable-model-invocation: false) but not combined with other red flags.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install bidding-analysis-report - After installation, invoke the skill by name or use
/bidding-analysis-report - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of bidding-analysis-report.
- Generates bidding data analysis reports (AI project proportion, annual trends, TOP institution rankings)
- Supports both Word and PDF output with embedded high-quality charts
- Provides automated donut and bar chart creation with a modern tech style
- Customizable for university, government, and enterprise procurement scenarios
- Input via Excel file, with flexible AI keyword recognition
- Includes ranking and trend analysis features for institutions
Metadata
Frequently Asked Questions
What is Bidding Analysis Report?
招标数据分析报告生成技能 - 支持AI项目占比分析、年度趋势分析、TOP机构排名,自动生成Word/PDF报告,嵌入高质量图表。适用于高校招标、政府采购、企业采购等场景。 It is an AI Agent Skill for Claude Code / OpenClaw, with 101 downloads so far.
How do I install Bidding Analysis Report?
Run "/install bidding-analysis-report" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Bidding Analysis Report free?
Yes, Bidding Analysis Report is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Bidding Analysis Report support?
Bidding Analysis Report is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Bidding Analysis Report?
It is built and maintained by Austin0208 (@austin0208); the current version is v1.0.0.
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