BioSkill

Perform normalized filesystem operations (list, read, write, append, mkdir, stat, copy, move, delete, search, replace) through a single skill script. Use when tasks require deterministic file manipulation through get_skill_script instead of built-in FileTools.

Execute Python snippets or Python files through a normalized skill entrypoint with explicit cwd, timeout, and argv. Use when tasks require ad-hoc Python execution and you want skill-based execution instead of built-in PythonTools.

Execute shell commands through a normalized skill entrypoint with explicit cwd and timeout. Use when tasks require command-line operations (tests, build, git, search, file inspection) and you want script-based execution via get_skill_script instead of built-in ShellTools.

Convert AlphaFold3 official inference JSON into Protenix, Boltz, or OpenFold3 inputs with schema validation. Use when an existing AF3 JSON must be reused by another folding stack, including batch conversion, target auto-detection from output filename, and best-effort mapping of AF3 `bondedAtomPairs`, MSA fields, templates, and ligand CCD/smiles data.

Convert CSV tables into valid AlphaFold3 input JSONs. Use this skill when you need to batch-generate AF3 JSONs from tabular inputs and run in MSA-free mode (protein uses empty unpairedMsa/pairedMsa, RNA uses empty unpairedMsa).

Extract deduplicated protein, DNA, and RNA sequences from AF3 or Protenix inference JSON files into per-entity-type FASTA files keyed by SHA-256 hash. Use as the first stage of the MSA pipeline before `af3-msa-search` and `af3-msa-injector`.

Inject cleaned ColabFold MSA artifacts from `af3-msa-search` into MSA-free AF3 or Protenix inference JSON files to produce complete inputs for downstream inference. Use when AF3 JSON contains empty `unpairedMsa`/`pairedMsa` fields or Protenix JSON lacks `unpairedMsaPath`/`pairedMsaPath`, including single-file and batch directory processing.

Run ColabFold MSA search from a FASTA file and automatically clean resulting A3M files into paired/unpaired outputs for downstream AF3-style pipelines.

Convert a single PDB/mmCIF structure into a validated AlphaFold3 JSON (alphafold3 dialect) by extracting polymer sequences, PTM/base modifications, ligands or ions (CCD codes), and optional bondedAtomPairs. Use when AF3 inputs must be rebuilt from solved structures while preserving chemistry.

Run reproducible structure-prediction workflows across AlphaFold3, Protenix, OpenFold3, and Boltz with a single Docker CLI and traceable run metadata. Use when backend-native inputs are already prepared (for example via af3-json-factory or af3-structure-json plus af3-json-converter), and you need multi-backend orchestration, dry-run command validation, or consistent run artifacts for scientific analysis.