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The skill's code, data, and runtime instructions match its stated purpose (a static China components sourcing guide); it requires no secrets or installs and does not attempt unexpected actions.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「China Electronic Components Sourcing」。简介：Comprehensive electronic components industry sourcing guide for international b…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1970168137/china-electronic-components-sourcing/SKILL.md
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SKILL.md

打开原始 SKILL.md（GitHub raw）

---
name: china-electronic-components-sourcing
version: 1.0.0
description: "Comprehensive electronic components industry sourcing guide for international buyers – provides detailed information about China's semiconductor, passive component, PCB, connector, and sensor manufacturing clusters, supply chain structure, regional specializations, and industry trends (2026 updated)."
author: "sourcing-china"
tags:
  - electronic-components
  - semiconductors
  - passives
  - PCBs
  - connectors
  - sourcing
  - supply-chain
invocable: true
---

# 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:**
```python
from do import get_industry_overview
result = get_industry_overview()
# Returns: industry scale, 2026 targets, automation rates, key drivers, etc.
```

### `get_supply_chain_structure() -> Dict`
Returns the complete electronic components supply chain structure (upstream, midstream, downstream).

**Example:**
```python
from do import get_supply_chain_structure
result = get_supply_chain_structure()
# Returns: raw materials, manufacturing, application industries
```

### `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:**
```python
from do import get_regional_clusters
all_clusters = get_regional_clusters()
yangtze = get_regional_clusters("Yangtze River Delta")
```

### `find_clusters_by_specialization(specialization: str) -> List[Dict]`
Find clusters that specialize in a given component type.

**Example:**
```python
from do import find_clusters_by_specialization
results = find_clusters_by_specialization("automotive semiconductors")
```

### `get_subsector_info(subsector: str) -> Dict`
Return detailed information about a specific electronic components subsector.

**Example:**
```python
from do import get_subsector_info
mlcc_info = get_subsector_info("MLCC")
semiconductor_info = get_subsector_info("semiconductors")
```

### `get_sourcing_guide() -> Dict`
Return supplier evaluation and sourcing best practices.

**Example:**
```python
from do import get_sourcing_guide
guide = get_sourcing_guide()
# Returns: evaluation criteria, verification methods, communication tips
```

### `get_faq(question: Optional[str] = None) -> Union[List[Dict], Dict]`
Return FAQ list or answer to a specific question.

**Example:**
```python
from do import get_faq
all_faqs = get_faq()
moq_faq = get_faq("MOQ")
```

### `get_glossary(term: Optional[str] = None) -> Union[Dict, str]`
Return glossary of terms or definition of a specific term.

**Example:**
```python
from do import get_glossary
all_terms = get_glossary()
mlcc_def = get_glossary("MLCC")
```

### `search_data(query: str) -> List[Dict]`
Simple search across all data for a query string.

**Example:**
```python
from do import search_data
results = search_data("automotive")
```

### `get_metadata() -> Dict`
Return metadata about the data source and last update.

**Example:**
```python
from do import get_metadata
meta = get_metadata()
```