tessl install tessl/pypi-rdkit@2024.9.0Platform wheels for RDKit - a comprehensive cheminformatics and machine-learning library with Python bindings
Agent Success
Agent success rate when using this tile
89%
Improvement
Agent success rate improvement when using this tile compared to baseline
1.01x
Baseline
Agent success rate without this tile
88%
{
"context": "This evaluation assesses the engineer's proficiency in using RDKit's aromaticity detection and manipulation capabilities. The focus is on correct usage of RDKit functions for counting aromatic rings, converting between aromatic and Kekule forms, and proper molecular handling.",
"type": "weighted_checklist",
"checklist": [
{
"name": "SMILES parsing",
"description": "Uses rdkit.Chem.MolFromSmiles() to parse SMILES strings into molecule objects, with proper error handling for invalid inputs",
"max_score": 15
},
{
"name": "Aromatic ring counting",
"description": "Uses rdkit.Chem.Descriptors.NumAromaticRings() or equivalent to count aromatic rings in molecules",
"max_score": 20
},
{
"name": "Kekule conversion",
"description": "Uses rdkit.Chem.MolToSmiles() with kekuleSmiles=True parameter to generate Kekule form SMILES with explicit single and double bonds",
"max_score": 25
},
{
"name": "Aromatic SMILES",
"description": "Uses rdkit.Chem.MolToSmiles() with default or kekuleSmiles=False to generate aromatic form SMILES notation",
"max_score": 20
},
{
"name": "Molecule sanitization",
"description": "Properly handles molecule sanitization (implicit in MolFromSmiles or explicit with SanitizeMol) to ensure aromaticity is correctly perceived",
"max_score": 10
},
{
"name": "Error handling",
"description": "Correctly raises ValueError when encountering invalid SMILES strings, checking for None return from MolFromSmiles()",
"max_score": 10
}
]
}