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auto-alphafold3
auto-alphafold3 enthält 5 gesammelte Skills von ashtonchew, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.
Skills in diesem Repository
Use when acting as the auto-AlphaFold3 autoresearch agent: read baseline metrics and Fold Cartographer diagnostics, choose one diagnostic target and one move family, propose or patch only the allowed AlphaFold3-lite model/training/sampler surface, and hand one trial to the orchestrator without touching Modal infrastructure or locked benchmark files.
Use when operating as a bounded auto-AlphaFold3 subagent worker that produces one proposal artifact for an assigned diagnostic target or move family, supports fast parallel hypothesis fanout, and never submits trials, calls Modal, edits locked files, appends ledgers, or integrates its own result.
Use when validating and submitting exactly one auto-AlphaFold3 AutoFoldTrial JSON through the approved local orchestrator command, rejecting direct Modal calls, locked benchmark paths, hidden-validation search, missing hypotheses, and multi-trial submissions.
Use when interpreting auto-AlphaFold3 scorer diagnostics into exactly one Fold Cartographer failure target, preserving best_val_calpha_lddt as the primary objective and mapping local geometry, long-range topology, distogram-vs-3D, or stability/compute evidence to safe move-family suggestions.
Use when a task depends on current Modal Python APIs, migration guidance, deployed object lookup, or docs-backed runtime behavior.