industrial retrosynthesis planning pipeline for target SMILES; run AiZynthFinder, normalize route JSON, query route molecules, rank routes, render figure-style route dashboards, and write analyst reports with retrosynthetic rationale.
ADMET-guided genetic molecule optimization workflow from seed SMILES; use when the agent needs to build or run an RDKit/SA-Score/ADMET-AI GA pipeline for molecule optimization, enforce molecule lineage logs, render optimization-history HTML dashboards, and write candidate triage reports.
Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.
Audit tabular datasets before analysis or training for schema drift, missing values, duplicate rows or IDs, target imbalance, and entity or group leakage across splits using pure-stdlib helpers.
Structure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source AlphaFold3 alternative with optional binding-affinity prediction.
Predict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA sequence with Borzoi. Use this skill when: (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding variants by predicted track delta.
HARD-LOCKED Catalyst-Design-Agent FAIRChem UMA (uma-s-1p1, oc20) SAC SAR screening for dissolution potential / adsorption / overpotential. Always call run_pipeline with the user's metals/metrics into a fresh workdir and present ONLY that run's result["deliverables"]. FORBIDDEN to return committed demo shells (metal_center_dissolution_*) as user results. FORBIDDEN tabular/heuristic/other MLIPs. If HF_TOKEN or hub unreachable, STOP and ask (HF_TOKEN / HF_ENDPOINT). Keywords: MLFF, UMA, OC20, catagent, M–N4, dissolution, graphene.
Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.