技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
input-data-formats【数据与研究】Author, validate, and debug Chai FASTA input records for proteins, ligands, DNA, RNA, modified residues, entity names, and chain naming.
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Use this sub-skill when an agent needs to create or repair Chai input FASTA records before folding. It covers entity headers, sequences, ligand SMILES, modified residues, entity names, and the chain-name consequences of fasta_names_as_cif_chains / entity_name_as_subchain.
chai-lab fold or chai_lab.chai1.run_inference after the FASTA is valid? Use ../cli-inference/SKILL.md..aligned.pqt, A3M conversion, MSA server, or template hit files? Use ../msa-templates/SKILL.md.../restraints-glycans/SKILL.md.glycan|name FASTA routing? This sub-skill covers the header; glycan string semantics belong to ../restraints-glycans/SKILL.md.>protein|name, >protein|name=receptor, >ligand|name=atp, >dna|name=primer, >rna|name=guide, or >glycan|name=n_linked.A/C/G/T records are ambiguous across DNA, RNA, and protein.AAA(SEP)AAA or (MSE)G, not as unbracketed three-letter text.[Mg+2] or [Zn+2], because bare ion text can pass header parsing but fail ligand tokenization.fasta_names_as_cif_chains=True uses entity names as parsing/output chain IDs.Run the bundled helper before expensive inference:
python scripts/validate_chai_fasta.py input.fasta
python scripts/validate_chai_fasta.py --tokenize --entity-names-as-subchains input.fasta
The first command checks Chai header parsing, required names, duplicate names, type heuristics, and polymer modified-residue syntax. The optional tokenization check catches malformed SMILES and chain-name issues that only appear when Chai builds chains.
references/fasta-and-entities.md — format grammar, entity tables, naming rules, and chain-name implications.references/api-reference.md — validation and parsing APIs useful for scripts and diagnostics.references/troubleshooting.md — common parser, sequence, ligand, duplicate-name, and chain-name failures.