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name: output-interpretation description: "Explain and validate AlphaFold 3 output directories, ranking/confidence files, optional embeddings/distograms, compression, and output-oriented troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

AlphaFold 3 Output Interpretation

Use this sub-skill when a user asks what an AlphaFold 3 result directory contains, whether a run produced expected outputs, how to choose a prediction, or why optional output files are missing or compressed.

Quick Routing

• For constructing AlphaFold 3 input JSON, sequence/entity IDs, seeds, or model/data JSON fields, use ../input-preparation/.
• For CLI flags such as --save_embeddings, --save_distogram, --compress_large_output_files, --force_output_dir, or separate data/inference runs, use ../running-predictions/.
• For writer functions, model runner APIs, and programmatic output generation, use ../python-apis/.
• For reading completed job directories, confidence metrics, ranking, embeddings, distograms, and output triage, stay here.

Core References

• references/output-files.md describes expected job directory layout, sanitized naming, required and optional files, sample/seed subdirectories, and zstandard compression behavior.
• references/confidence-metrics.md explains ranking_score, pLDDT, PAE, pTM, ipTM, chain and chain-pair metrics, and antibody-antigen interface ranking.
• references/troubleshooting.md covers missing files, absent embeddings/distograms, low rankings or clashes, compressed large files, output directory collisions, and low-confidence predictions.

Inspect Outputs Quickly

Run the bundled script on a completed AlphaFold 3 job directory:

python scripts/summarize_outputs.py /path/to/job_output

The script uses only the Python standard library. It reports expected top-level files, seed/sample directories, optional embedding/distogram directories, .npz member names when available, ranking_scores.csv rows, and keys from summary confidence JSON files. It does not import AlphaFold 3 and does not decompress .zst files.

Interpretation Checklist

1. Identify the job directory name and sanitized job prefix; top-level result files normally use that prefix.
2. Confirm one seed-<seed>_sample-<sample> directory per seed/sample prediction, each with a model CIF, full confidences JSON, and summary confidences JSON.
3. Use top-level <job>_ranking_scores.csv to find the highest ranking_score; the top-level <job>_model.cif and confidence files are copied from that best-ranked sample.
4. Use summary confidences for ranking and overview metrics; use full confidences for per-atom pLDDT, PAE, contacts, and chain IDs.
5. Treat embeddings and distograms as optional: they appear only when the corresponding save flags were enabled, and they can be very large.
6. If .cif.zst or _confidences.json.zst files appear, the run used compression for large output files; summary JSON, ranking CSV, terms, embeddings, and distograms remain normally readable.