byted-bytehouse-data-asset-analyzer
基于ByteHouse MCP Server，生成数据资产目录和血缘分析的技能，用于获取数据库表结构、生成数据资产目录、分析表之间的血缘关系。当用户需要获取ByteHouse数据库的表结构、生成数据资产目录、分析表之间的血缘关系时，使用此Skill。
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Install
Works with every agent the skills CLI supports.
npx skills add https://skills.volces.com --skill byted-bytehouse-data-asset-analyzer- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads byted-bytehouse-data-asset-analyzer automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
ByteHouse 数据资产和血缘分析 Skill
描述
本Skill基于ByteHouse MCP Server，生成数据资产目录和血缘分析的技能。
当以下情况时使用此 Skill: (1) 需要获取数据库表结构和字段信息 (2) 需要生成数据资产目录 (3) 需要分析表之间的血缘关系 (4) 用户提到"数据资产"、"血缘分析"、"表结构"、"字段分析"
前置条件
- Python 3.8+
- uv (已安装在
/root/.local/bin/uv) - ByteHouse MCP Server Skill - 本skill依赖
bytehouse-mcpskill提供的ByteHouse访问能力
依赖关系
本skill依赖 bytehouse-mcp skill，使用其提供的MCP Server访问ByteHouse。
确保 bytehouse-mcp skill已正确配置并可以正常使用。
📁 文件说明
- SKILL.md - 本文件，技能主文档
- data_asset_analyzer.py - 数据资产和血缘分析主程序
- README.md - 快速入门指南
配置信息
ByteHouse连接配置
本skill复用 bytehouse-mcp skill的配置。请确保已在 bytehouse-mcp skill中配置好
🎯 功能特性
1. 完整Schema获取
- 获取指定数据库的所有表
- 获取每张表的所有字段
- 提取表引擎、注释等元数据
- 解析CREATE TABLE语句
2. 数据资产目录生成
- 表统计（总表数、总列数）
- 引擎分布统计
- 自动标签生成
- 表资产详情
3. 血缘分析
- 表关系识别（Distributed → Local）
- 列相似性分析
- 关系可视化
🚀 快速开始
方法1: 运行数据资产和血缘分析
# 先设置环境变量（复用bytehouse-mcp的配置）
source scripts/export_config.sh
# 运行分析工具
uv run scripts/data_asset_analyzer.py
分析内容包括：
- 数据库完整schema（所有表和字段）
- 数据资产目录（表统计、引擎分布、自动标签）
- 血缘分析（表关系、列相似性）
输出文件（保存在 output/ 目录）：
schema_{database}_{timestamp}.json- 完整的数据库schemacatalog_{database}_{timestamp}.json- 数据资产目录lineage_{database}_{timestamp}.json- 血缘分析报告
💻 程序化使用
使用分析器模块
#!/usr/bin/env python3
# /// script
# dependencies = [
# "mcp>=1.0.0",
# ]
# ///
import asyncio
import sys
import os
# 添加bytehouse-mcp skill的路径
BYTEHOUSE_MCP_PATH = os.path.join(
os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
"bytehouse-mcp"
)
sys.path.insert(0, BYTEHOUSE_MCP_PATH)
from data_asset_analyzer import DataAssetAnalyzer
async def main():
analyzer = DataAssetAnalyzer()
await analyzer.connect()
# 分析数据库
result = await analyzer.analyze_database("default")
# result 包含:
# - schema: 完整的数据库schema
# - catalog: 数据资产目录
# - lineage: 血缘分析
# - files: 生成的文件路径
asyncio.run(main())
📊 输出文件说明
1. Schema文件 (schema_*.json)
包含数据库的完整结构：
{
"database": "default",
"analyzed_at": "2026-03-12T19:50:00",
"tables": [
{
"name": "conversation_feedback",
"comment": "",
"engine": "Distributed",
"columns": [
{
"name": "session_id",
"type": "String",
"comment": ""
}
],
"create_table_query": "CREATE TABLE ..."
}
]
}
2. 数据资产目录 (catalog_*.json)
包含数据资产的统计信息：
{
"database": "default",
"generated_at": "2026-03-12T19:50:00",
"summary": {
"total_tables": 8,
"total_columns": 45,
"engines": {
"Distributed": 4,
"HaMergeTree": 3,
"MergeTree": 1
}
},
"tables": [
{
"name": "conversation_feedback",
"comment": "",
"engine": "Distributed",
"column_count": 10,
"columns": [...],
"tags": ["distributed", "user-feedback"]
}
]
}
3. 血缘分析 (lineage_*.json)
包含表关系和列相似性：
{
"database": "default",
"generated_at": "2026-03-12T19:50:00",
"table_relationships": [
{
"source_table": "conversation_feedback",
"relationships": [
{
"type": "distributed_to_local",
"target_table": "conversation_feedback_local",
"description": "Distributed表指向Local表"
}
]
}
],
"column_similarities": [
{
"column_name": "session_id",
"column_type": "String",
"found_in_tables": [
"conversation_feedback",
"conversation_feedback_local"
]
}
]
}
🏷️ 自动标签生成
分析器会根据表名和引擎自动生成标签：
| 标签 | 说明 |
|---|---|
merge-tree | 使用MergeTree引擎 |
distributed | 使用Distributed引擎 |
high-availability | 使用HaMergeTree或HaUniqueMergeTree |
log-table | 表名包含"log" |
user-feedback | 表名包含"feedback" |
local-table | 表名以"_local"结尾 |
test-table | 表名包含"test" |
📚 更多信息
详细使用说明请参考 bytehouse-mcp skill
最后更新: 2026-03-12
FAQ
What does the byted-bytehouse-data-asset-analyzer skill do?
基于ByteHouse MCP Server，生成数据资产目录和血缘分析的技能，用于获取数据库表结构、生成数据资产目录、分析表之间的血缘关系。当用户需要获取ByteHouse数据库的表结构、生成数据资产目录、分析表之间的血缘关系时，使用此Skill。
How do I install byted-bytehouse-data-asset-analyzer?
Run npx skills add https://skills.volces.com --skill byted-bytehouse-data-asset-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/byted-bytehouse-data-asset-analyzer/ (personal) or .claude/skills/byted-bytehouse-data-asset-analyzer/ (project).
Which AI agents can use byted-bytehouse-data-asset-analyzer?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is byted-bytehouse-data-asset-analyzer safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains byted-bytehouse-data-asset-analyzer?
It is published by skills.volces.com in skills.volces.com. It has 311 recorded installs.
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