excel-field-analyzer
分析Excel/CSV字段结构，AI自动生成中英文映射，验证翻译质量，输出统计报告。用于电子表格分析、数据字典创建、字段映射场景。
Best use case
excel-field-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
分析Excel/CSV字段结构，AI自动生成中英文映射，验证翻译质量，输出统计报告。用于电子表格分析、数据字典创建、字段映射场景。
Teams using excel-field-analyzer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/excel-field-analyzer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How excel-field-analyzer Compares
| Feature / Agent | excel-field-analyzer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
分析Excel/CSV字段结构，AI自动生成中英文映射，验证翻译质量，输出统计报告。用于电子表格分析、数据字典创建、字段映射场景。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Excel/CSV 字段分析器
## 概述
智能分析 Excel 与 CSV 文件，自动生成中英文字段映射、统计报告与 HTML 可视化。
**核心能力：**
- 字段统计分析（空值率、唯一值、分布）
- AI 字段映射（内置 50+ 车险领域字段）
- 映射质量自动校验
- HTML 可视化报告
## 快速开始
### 对话式调用（推荐）
直接与 Claude 对话：
```
"帮我分析这个 Excel 文件的字段"
"分析 ./data/insurance_data.xlsx 的字段映射"
```
### 命令行
```bash
# 基础分析
python scripts/analyzer.py <file_path> [output_dir] [topn]
# 示例
python scripts/analyzer.py data.xlsx ./output 10
# 支持格式：.xlsx, .xls, .csv, .txt
```
## 核心特性
### 1. 预置映射库
- **车险领域**：内置 50+ 字段映射
- **覆盖范围**：财务、车辆、机构、产品、时间
- **示例**：
- `商业险保费` → `commercial_premium`（finance/number）
- `三级机构` → `org_level_3`（organization/string）
- `确认时间` → `time_confirm`（time/datetime）
### 2. AI 批量学习
- **零人工**：自动为未知字段生成映射
- **智能分析**：语义分析 + 数据样本推断
- **自动保存**：结果保存至 `custom.json` 便于复用
- **高准确率**：70 字段测试集准确率 100%
**示例：**
```
🔍 Found 70 unknown fields
💡 Using AI to generate mappings...
✅ Generated 70 mappings and saved to custom.json
- 刷新时间 → time_refresh [time/datetime]
- 交叉销售标识 → flag_cross_sales [flag/string]
- 签单保费 → premium_signing [finance/number]
```
### 3. 质量校验
- **自动检查**：4 个维度（命名、分组、语义、类型）
- **质量评分**：优秀（≥90）/ 良好（75-89）/ 一般（60-74）/ 较差（<60）
- **详细报告**：Markdown，附改进建议
### 4. 交互式学习
- **手动模式**：可选，精确控制字段映射
- **引导流程**：逐步选择英文字段名、分组、类型
- **持久存储**：全部学习映射保存至 `custom.json`
## 输出文件
### 1. HTML 可视化报告
- 文件元信息与生成时间
- 每个工作表的完整统计表
- 数值统计与 Top 值分布
- 交互式探索
### 2. JSON 字段映射表
```json
{
"field_name": "commercial_premium",
"cn_name": "商业险保费",
"group": "finance",
"dtype": "number",
"role": "measure",
"aggregation": "sum",
"is_mapped": true
}
```
### 3. 质量校验报告（Markdown）
- 总体质量统计
- 需复审字段与建议
- 优秀映射示例
- 质量分布可视化
## 业务分组
| 分组 | 描述 | 示例 |
|------|------|------|
| finance | 财务数据 | 保费、赔款、费用 |
| organization | 机构信息 | 三级机构、四级机构 |
| vehicle | 车辆相关 | 车牌、车型 |
| product | 产品信息 | 险类、险种 |
| time | 时间字段 | 确认时间、起保日期 |
| flag | 状态标识 | 续保标识、新能源标识 |
| partner | 合作方信息 | 4S 集团、经销商 |
| general | 通用字段 | 业务类型、客户类别 |
## 文档
- **reference.md** - 完整技术文档、配置细节、API 参考
- **examples.md** - 代码示例、使用场景、集成指南
## 版本历史
### v2.3 (2025-11-23) - 质量保障
- 🔍 映射质量校验体系
- 4 个校验维度与质量评分
- 自动生成质量报告
### v2.2 (2025-11-23) - AI 批量学习
- 🤖 AI 驱动的自动字段映射
- 语义分析 + 数据样本推断
- 测试数据集准确率 100%
### v2.1 (2025-11-23)
- ✨ 支持 CSV 文件
- 统一 Excel 与 CSV 接口
### v2.0 (2025-11-23)
- ✨ Claude Code Skill 架构
- 多源配置系统
- 交互式字段学习
## 依赖
```bash
pip install pandas openpyxl numpy
```
## 许可证
MIT 许可证Related Skills
ab-testing-analyzer
全面的AB测试分析工具，支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果，提供统计显著性检验和深度洞察。
video-analyzer
鏅鸿兘鍒嗘瀽 Bilibili/YouTube/鏈湴瑙嗛锛岀敓鎴愯浆鍐欍€佽瘎浼板拰鎬荤粨銆傛敮鎸佸叧閿抚鎴浘鑷姩宓屽叆銆?
edu-video-analyzer
Analyze educational YouTube channels for classroom adoption potential, curriculum alignment, and pedagogical effectiveness. Use when comparing educational video content (like MRU vs Crash Course), evaluating teaching methodologies, identifying content gaps for course design, or developing educational video strategy focused on student learning outcomes rather than monetization.
blog-voice-analyzer
Run the AI Voice Analyzer on blog content to detect AI-sounding patterns and get actionable rewrite suggestions. Use when reviewing or improving blog articles before publishing.
springfield-max
Simpsons-themed autonomous workflow orchestrator v7.0 for platform building. Powered by Opus 4.6 Agent Teams, 1M context, adaptive thinking, and effort levels. 17 characters, full MCP access, 50 iteration limits, orchestrator promises, and mandatory quality gates. Domain-agnostic - works for any software platform.
ecommerce-competitor-analyzer
Multi-platform e-commerce competitor analysis skill that automatically scrapes product data from Amazon, Temu, Shopee and generates comprehensive analysis reports using AI. Use when you need to analyze competitor products, extract product insights, or batch analyze multiple product listings. Supports bulk processing with structured outputs including title, price, rating, reviews, and strategic analysis.
api-spec-analyzer
Analyzes API documentation from OpenAPI specs to provide TypeScript interfaces, request/response formats, and implementation guidance. Use when implementing API integrations, debugging API errors (400, 401, 404), replacing mock APIs, verifying data types, or when user mentions endpoints, API calls, or backend integration.
api-schema-analyzer
Analyze OpenAPI and Postman schemas for MCP tool generation. Use when analyzing API specifications, extracting endpoint information, generating tool signatures, or when user mentions OpenAPI, Swagger, API schema, endpoint analysis.
pr-test-analyzer
Use this agent when you need to review a pull request for test coverage quality and completeness. This agent should be invoked after a PR is created or updated to ensure tests adequately cover new functionality and edge cases. Examples:\n\n<example>\nContext: Daisy has just created a pull request with new functionality.\nuser: "I've created the PR. Can you check if the tests are thorough?"\nassistant: "I'll use the pr-test-analyzer agent to review the test coverage and identify any critical gaps."\n<commentary>\nSince Daisy is asking about test thoroughness in a PR, use the Task tool to launch the pr-test-analyzer agent.\n</commentary>\n</example>\n\n<example>\nContext: A pull request has been updated with new code changes.\nuser: "The PR is ready for review - I added the new validation logic we discussed"\nassistant: "Let me analyze the PR to ensure the tests adequately cover the new validation logic and edge cases."\n<commentary>\nThe PR has new functionality that needs test coverage analysis, so use the pr-test-analyzer agent.\n</commentary>\n</example>\n\n<example>\nContext: Reviewing PR feedback before marking as ready.\nuser: "Before I mark this PR as ready, can you double-check the test coverage?"\nassistant: "I'll use the pr-test-analyzer agent to thoroughly review the test coverage and identify any critical gaps before you mark it ready."\n<commentary>\nDaisy wants a final test coverage check before marking PR ready, use the pr-test-analyzer agent.\n</commentary>\n</example>
analyzer-agent
Static analysis, code quality checks, and security scanning agent
ai-transcript-analyzer
Analyze transcript files using OpenAI API (gpt-5-mini) to extract insights, summaries, key topics, quotes, and action items. This skill should be used when users have transcript files (from WhisperKit, YouTube, podcasts, meetings, etc.) and want AI-powered analysis, summaries, or custom insights extracted from the content. Supports both default comprehensive analysis and custom prompts for specific information extraction.
agent-chain-analyzer
Detects and analyzes agent chain anti-patterns where agents invoke other agents sequentially causing massive context load