القائمة
Encode molecule SMILES columns into RDKit descriptor features for BO.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | bo-encode-molecule-descriptors |
| description | Encode molecule SMILES columns into RDKit descriptor features for BO. |
Use this skill when the user has a CSV with one or more molecule SMILES columns and wants to convert it into numerical descriptor features for the BO engine.
uv run python -m bo_workflow.converters.molecule_descriptors encode \
--input <CSV_PATH> --output-dir <DIR> --smiles-cols <COL1> [<COL2> ...]
Optional flags: --morgan-bits <N> (default 64).
features_csv — path to descriptor features CSV (descriptor/fingerprint columns + passthrough columns)catalog_csv — path to catalog CSV (same descriptors + original SMILES columns for decode)rows — number of rows encodeddescriptor_columns — number of descriptor columns generatedpassthrough_columns — non-SMILES columns carried through from the inputfeatures.csv is ready for init --dataset.catalog.csv is required by decode to map BO suggestions back to real molecules.Orchestrate an end-to-end chemistry or materials optimization study from a plain-English research question to BO execution and a paper draft.
BO execution layer — initializes a run from a resolved experiment spec, records observations, and continues through suggest/observe/report.
Initialize a BO run from a dataset or explicit search-space JSON.
Generate a final BO report and summarize optimization status.
Run an external evaluator loop for a BO run using a pre-provisioned backend id.
Design and stabilize an expensive or fragile chemistry evaluator before BO setup.