计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
structure-prediction【效率与协作】Plan and validate PaddleHelix HelixFold structure-prediction workflows without unsafe downloads or GPU inference.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when a request mentions HelixFold3 input JSON, HelixFold inference, MSA or database paths, checkpoint placement, bf16 versus fp32, protein structure output files, or HelixFold-S1 modules.
Do not download genetic databases or model weights, launch training, launch GPU/DCU inference, mutate a user environment, or invoke original repository launch scripts as a default action. If the user explicitly approves execution, construct a command from the bundled references after validating local paths and runtime prerequisites. Reduced HelixFold3/S1 databases are hundreds of GB after extraction, and the inference commands assume a compatible PaddlePaddle GPU stack plus MSA binaries.
Safe default actions:
scripts/validate_helixfold3_input.py before planning any run.The lightweight PaddleHelix inspection environment is not a HelixFold runtime environment. Treat PaddlePaddle GPU, MSA tools, OpenMM/PDBFixer, pgl, RDKit, model checkpoints, and genetic databases as optional workflow dependencies that must be planned and confirmed before use.
references/helixfold3.md.references/helixfold-family.md.references/data-formats.md.bf16, token/memory limits, or missing checkpoints, read references/troubleshooting.md.../protein-sequence-function/SKILL.md.../compound-drug-discovery/SKILL.md.Run this only as a local JSON/schema preflight; it does not import Paddle, download data, or start inference:
python scripts/validate_helixfold3_input.py --help
python scripts/validate_helixfold3_input.py input.json --mode helixfold3 --max-tokens 1200
python scripts/validate_helixfold3_input.py input.json --mode helixfold-s1
Use --mode helixfold-s1 when validating the S1 top-level fields (job_name, recycle, ensemble, model_type), s1_sample_constraint, S1 sidechain replacements, and the S1 multi-chain expectation. Use --strict-sequence-alphabet only when the user wants alphabet-level rejection rather than warnings.
fp32 on V100-class GPUs; use bf16 only on hardware known to support it, such as A100/H100-class GPUs.infer_times, diffusion batch size, token count, and subbatch/recycle settings conservative when planning for 32 GB GPUs.full_dbs support for HelixFold3/S1 as unavailable unless the user has current evidence that their local version supports it; documented reduced databases are already large.