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Use for external data access via pymatgen.ext: Materials Project (MPRester), OPTIMADE endpoints, and COD lookups.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | pymatgen-ext |
| description | Use for external data access via pymatgen.ext: Materials Project (MPRester), OPTIMADE endpoints, and COD lookups. |
| metadata | {"short-description":"pymatgen external data"} |
Pymatgen external data helpers provide access to Materials Project, OPTIMADE endpoints, and COD structures.
Ensure pymatgen is installed in your Python environment:
pip install pymatgen mp-api
# or
conda install -c conda-forge pymatgen mp-api
Example usage pattern:
from mp_api.client import MPRester
# your code here
Structure and export as needed.Executable examples in the scripts/ directory:
2013-01-01-Calculating_Reaction_Energies_with_the_Materials_API.py - Reaction energies using Materials Project data.2013-01-01-Plotting_and_Analyzing_a_Phase_Diagram_using_the_Materials_API.py - Phase diagram plotting and analysis with MP data.2017-03-02-Getting_data_from_Materials_Project.py - Querying Materials Project for structures and data.2018-09-25-Structure_Prediction_using_Pymatgen_and_the_Materials_API.py - Structure prediction with Materials Project data.Note: These scripts require Materials Project API access; set your API key before running.
Detailed reference material (load as needed):
references/external-data.md - External data access patternsreferences/docs/pymatgen.ext.md - Local API docsStructured brainstorming and ideation facilitation using proven creativity techniques. Use when users want to generate ideas, explore solutions, break through creative blocks, or need facilitated ideation sessions. Triggers include requests like 'help me brainstorm,' 'generate ideas for,' 'creative solutions to,' or 'think of alternatives.'
Use when investigating why something happened and need to distinguish correlation from causation, identify root causes vs symptoms, test competing hypotheses, control for confounding variables, or design experiments to validate causal claims. Invoke when debugging systems, analyzing failures, researching health outcomes, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"
Use when comparing multiple named alternatives across several criteria, need transparent trade-off analysis, making group decisions requiring alignment, choosing between vendors/tools/strategies, stakeholders need to see decision rationale, balancing competing priorities (cost vs quality vs speed), user mentions "which option should we choose", "compare alternatives", "evaluate vendors", "trade-offs", or when decision needs to be defensible and data-driven.
Use when dealing with complex systems that need simplification, identifying bottlenecks or critical failure points, redesigning architecture or processes for better performance, breaking down problems that feel overwhelming, analyzing dependencies to understand ripple effects, user mentions "this is too complex", "where's the bottleneck", "how do we redesign this", "what are the key components", or when optimization requires understanding how parts interact.
Use when optimizing multi-factor systems with limited experimental budget, screening many variables to find the vital few, discovering interactions between parameters, mapping response surfaces for peak performance, validating robustness to noise factors, or when users mention factorial designs, A/B/n testing, parameter tuning, process optimization, or experimental efficiency.
Use when you have validated symmetry groups and need to design neural network architecture that respects those symmetries. Invoke when user mentions equivariant layers, G-CNN, e3nn, steerable networks, building symmetry into model, or needs architecture recommendations for specific symmetry groups. Provides architecture patterns and implementation guidance.