executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
prediction-cliGuide local AlphaFold prediction CLI workflows, flags, presets, MSA reuse, relaxation choices, random seeds, and output expectations.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when an agent needs to construct, review, or diagnose a local installed run_alphafold prediction command without launching full inference.
../docker-and-data-setup/.../input-data-and-formats/.ranking_debug.json, pLDDT, pTM, ipTM, and PAE interpretation to ../outputs-and-confidence/.../relaxation/.--fasta_paths basenames unique because each FASTA stem becomes the target output subdirectory.--use_precomputed_msas=true as a manual cache-reuse decision; AlphaFold does not prove the cached MSAs match the current sequence, databases, or flags.--random_seed as a reproducibility aid, not a determinism guarantee, because GPU inference and input data changes can still alter results.