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name: prediction-cli description: "Guide local AlphaFold prediction CLI workflows, flags, presets, MSA reuse, relaxation choices, random seeds, and output expectations." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

AlphaFold Prediction CLI

Use this sub-skill when an agent needs to construct, review, or diagnose a local installed run_alphafold prediction command without launching full inference.

Read First

• Start with references/cli-reference.md for required flags, preset compatibility, database path expectations, and output file patterns.
• Use references/workflows.md for complete direct-CLI command templates, MSA reuse, random seed handling, and Docker-to-direct CLI conversion.
• Use references/troubleshooting.md when a command fails before inference, produces surprising output folders, or misuses relaxation, benchmark, or MSA reuse flags.
• Run scripts/check_prediction_inputs.py to validate FASTA paths, duplicate target names, preset/database flag combinations, path expectations, and common safety caveats before proposing an inference run.

Routing Boundaries

• Route Docker image builds, container mounts, GPU runtime setup, and data download planning to ../docker-and-data-setup/.
• Route FASTA contents, sequence/MSA/template formats, parser behavior, and chain validation to ../input-data-and-formats/.
• Route PDB/mmCIF files, ranking_debug.json, pLDDT, pTM, ipTM, and PAE interpretation to ../outputs-and-confidence/.
• Route Amber/OpenMM internals, relaxation backend failures, and structural violation details to ../relaxation/.

Safe Operating Rules

• Do not run full AlphaFold inference as a validation step; it can require large databases, external tools, GPU memory, and hours of runtime.
• Prefer validating a command with the bundled dry-run checker, then hand the command to the user with explicit resource and database assumptions.
• Keep --fasta_paths basenames unique because each FASTA stem becomes the target output subdirectory.
• Treat --use_precomputed_msas=true as a manual cache-reuse decision; AlphaFold does not prove the cached MSAs match the current sequence, databases, or flags.
• Treat --random_seed as a reproducibility aid, not a determinism guarantee, because GPU inference and input data changes can still alter results.