China Electronic Components Sourcing Skill
Description
This skill helps international electronics buyers navigate China's electronic components manufacturing landscape, which is projected to exceed
¥5.2 trillion in revenue by 2026. It provides data-backed intelligence on regional clusters, supply chain structure, and industry trends based on the latest government policies and industry reports.
Key Capabilities
- - Industry Overview: Get a summary of China's electronic components industry scale and development targets.
- Supply Chain Structure: Understand the complete industry chain from raw materials to downstream applications.
- Regional Clusters: Identify specialized manufacturing hubs for different component types (semiconductors, passives, PCBs, connectors, sensors).
- Subsector Insights: Access detailed information on key subsectors (semiconductors, passive components, PCBs, connectors, sensors, etc.).
- Sourcing Recommendations: Get practical guidance on evaluating and selecting suppliers, including verification methods and communication best practices.
How to Use
You can interact with this skill using natural language. For example:
- - "What's the overall status of China's electronic components industry in 2026?"
- "Show me the supply chain structure for electronic components"
- "Which regions are best for sourcing automotive-grade semiconductors?"
- "Tell me about MLCC manufacturing clusters"
- "How do I evaluate PCB suppliers in China?"
- "What certifications should I look for in sensor suppliers?"
Data Sources
This skill aggregates data from:
- - Ministry of Industry and Information Technology (MIIT) official policies
- National Bureau of Statistics of China
- China Electronic Components Association (CECA) annual reports
- Industry research publications (updated Q1 2026)
Implementation
The skill logic is implemented in
do.py, which reads structured data from
data.json. All data is cluster-level intelligence without individual factory contacts.
API Reference
The following Python functions are available in do.py for programmatic access:
get_industry_overview() -> Dict
Returns overview of China's electronic components industry scale, targets, and key policy initiatives.
Example:
CODEBLOCK0
get_supply_chain_structure() -> Dict
Returns the complete electronic components supply chain structure (upstream, midstream, downstream).
Example:
CODEBLOCK1
get_regional_clusters(region: Optional[str] = None) -> Union[List[Dict], Dict]
Returns all regional clusters or a specific cluster by name.
- - If
region is None: returns list of all clusters - If
region is specified: returns that cluster's details
Example:
CODEBLOCK2
find_clusters_by_specialization(specialization: str) -> List[Dict]
Find clusters that specialize in a given component type.
Example:
CODEBLOCK3
get_subsector_info(subsector: str) -> Dict
Return detailed information about a specific electronic components subsector.
Example:
CODEBLOCK4
get_sourcing_guide() -> Dict
Return supplier evaluation and sourcing best practices.
Example:
CODEBLOCK5
get_faq(question: Optional[str] = None) -> Union[List[Dict], Dict]
Return FAQ list or answer to a specific question.
Example:
CODEBLOCK6
get_glossary(term: Optional[str] = None) -> Union[Dict, str]
Return glossary of terms or definition of a specific term.
Example:
CODEBLOCK7
search_data(query: str) -> List[Dict]
Simple search across all data for a query string.
Example:
CODEBLOCK8
get_metadata() -> Dict
Return metadata about the data source and last update.
Example:
CODEBLOCK9
中国电子元器件采购技能
描述
该技能帮助国际电子采购商了解中国电子元器件制造格局，预计到2026年该行业收入将超过
5.2万亿元人民币。基于最新政府政策和行业报告，提供关于区域集群、供应链结构和行业趋势的数据驱动情报。
核心能力
- - 行业概览：获取中国电子元器件行业规模和发展目标的摘要信息。
- 供应链结构：了解从原材料到下游应用的完整产业链。
- 区域集群：识别不同元器件类型（半导体、被动元件、PCB、连接器、传感器）的专业制造中心。
- 子行业洞察：获取关键子行业（半导体、被动元件、PCB、连接器、传感器等）的详细信息。
- 采购建议：获得评估和选择供应商的实用指导，包括验证方法和最佳沟通实践。
使用方法
您可以使用自然语言与该技能交互。例如：
- - 2026年中国电子元器件行业的整体状况如何？
- 展示电子元器件的供应链结构
- 哪些区域最适合采购汽车级半导体？
- 介绍一下MLCC制造集群
- 如何评估中国的PCB供应商？
- 传感器供应商应具备哪些认证？
数据来源
该技能汇总了以下数据：
- - 工业和信息化部（MIIT）官方政策
- 中国国家统计局
- 中国电子元件行业协会（CECA）年度报告
- 行业研究出版物（2026年第一季度更新）
实现方式
技能逻辑在do.py中实现，该文件读取data.json中的结构化数据。所有数据均为集群级情报，不包含单个工厂联系方式。
API参考
do.py中提供以下Python函数用于程序化访问：
getindustryoverview() -> Dict
返回中国电子元器件行业规模、目标和关键政策举措的概览。
示例：
python
from do import getindustryoverview
result = getindustryoverview()
返回：行业规模、2026年目标、自动化率、关键驱动因素等
getsupplychain_structure() -> Dict
返回完整的电子元器件供应链结构（上游、中游、下游）。
示例：
python
from do import getsupplychain_structure
result = getsupplychain_structure()
返回：原材料、制造、应用行业
getregionalclusters(region: Optional[str] = None) -> Union[List[Dict], Dict]
返回所有区域集群或按名称返回特定集群。
- - 如果region为None：返回所有集群列表
- 如果指定了region：返回该集群的详细信息
示例：
python
from do import getregionalclusters
allclusters = getregional_clusters()
yangtze = getregionalclusters(长江三角洲)
findclustersby_specialization(specialization: str) -> List[Dict]
查找专注于给定元器件类型的集群。
示例：
python
from do import findclustersby_specialization
results = findclustersby_specialization(汽车级半导体)
getsubsectorinfo(subsector: str) -> Dict
返回特定电子元器件子行业的详细信息。
示例：
python
from do import getsubsectorinfo
mlccinfo = getsubsector_info(MLCC)
semiconductorinfo = getsubsector_info(半导体)
getsourcingguide() -> Dict
返回供应商评估和采购最佳实践。
示例：
python
from do import getsourcingguide
guide = getsourcingguide()
返回：评估标准、验证方法、沟通技巧
get_faq(question: Optional[str] = None) -> Union[List[Dict], Dict]
返回常见问题列表或特定问题的答案。
示例：
python
from do import get_faq
allfaqs = getfaq()
moqfaq = getfaq(MOQ)
get_glossary(term: Optional[str] = None) -> Union[Dict, str]
返回术语表或特定术语的定义。
示例：
python
from do import get_glossary
allterms = getglossary()
mlccdef = getglossary(MLCC)
search_data(query: str) -> List[Dict]
在所有数据中简单搜索查询字符串。
示例：
python
from do import search_data
results = search_data(汽车)
get_metadata() -> Dict
返回关于数据源和最后更新的元数据。
示例：
python
from do import get_metadata
meta = get_metadata()
