a5c-ai/materials-database-querier
library/specializations/domains/science/nanotechnology/skills/materials-database-querier/SKILL.md
Materials database query skill for accessing structure and property data from multiple repositories
$ install --global
skillsauthnpx skillsauth add a5c-ai/babysitter materials-database-querierInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- materials-database-querier
- description:
- Materials database query skill for accessing structure and property data from multiple repositories
- specialization:
- nanotechnology
- domain:
- science
- category:
- computational
- priority:
- high
- phase:
- 6
Materials Database Querier
Purpose
The Materials Database Querier skill provides unified access to multiple materials databases for structure and property retrieval, enabling comprehensive materials search and data aggregation across repositories.
Capabilities
- Materials Project API integration
- AFLOW database queries
- ICSD/CSD structure retrieval
- NOMAD repository access
- Cross-database searches
- Property aggregation and comparison
Usage Guidelines
Database Query Workflow
-
Query Design
- Define search criteria
- Select target databases
- Set property filters
-
Data Retrieval
- Execute queries
- Handle pagination
- Aggregate results
-
Data Processing
- Standardize formats
- Compare across sources
- Export for analysis
Process Integration
- Machine Learning Materials Discovery Pipeline
- DFT Calculation Pipeline for Nanomaterials
- Structure-Property Correlation Analysis
Input Schema
{
"query_type": "composition|structure|property",
"databases": ["materials_project", "aflow", "icsd"],
"criteria": {
"elements": ["string"],
"property_range": {"property": "string", "min": "number", "max": "number"}
},
"limit": "number"
}
Output Schema
{
"materials": [{
"id": "string",
"formula": "string",
"structure_file": "string",
"properties": {
"bandgap": "number",
"formation_energy": "number"
},
"source": "string"
}],
"total_found": "number",
"query_metadata": {
"databases_searched": ["string"],
"query_time": "number"
}
}
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