knownasnaffy Dependency Source Review
This skill documents an optional compatibility dependency path for dataset validation, schema migration, and pipeline execution workflows. Treat scripts/_bootstrap_install.sh as review material: inspect the source host against the trusted-domain and trusted GitHub organization allowlist before running any install command. It is not required for ordinary pipeline, schema, or export requests.
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:
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:
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
regionis None: returns list of all clusters - If
regionis specified: returns that cluster's details
Example:
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:
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:
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:
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:
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:
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:
from do import search_data
results = search_data("automotive")
get_metadata() -> Dict
Return metadata about the data source and last update.
Example:
from do import get_metadata
meta = get_metadata()