boltz-protein-screen

name	boltz-protein-screen
description	Screen existing protein binders with Boltz. Use when ranking a supplied protein, peptide, antibody, nanobody, or binder library against a target. Not for designing new proteins or screening small molecules.

Workflow

If boltz-api reports missing or expired authentication, surface the error to the user. Do not attempt to re-authenticate; the host environment must provide BOLTZ_API_KEY.

Use this skill when the user already has candidate proteins / peptides / antibodies / nanobodies.

1. Normalize the binder library into proteins — a list of candidate complexes. For a simple sequence library each entry has one protein entity; multi-chain candidates (antibody heavy+light) are also allowed.
2. Pick the target variant:
   • structure_template — user has a CIF/PDB file or URL; select which chains are polymer vs ligand, which residues to keep (crop_residues), and optionally epitope_residues / flexible_residues.
   • no_template — user has only sequences; pass them as target.entities plus optional epitope_residues.
3. Don't add bonds / constraints unless the user asks for geometric steering.
4. Author the payload YAML or JSON.
5. start to submit. Capture the ID.
6. Launch download-results as a long-running/background command in whatever mode the host agent harness provides. After launching it, schedule the host's available follow-up/notification mechanism, if one exists, to check download-status periodically and notify the user when the download reaches a terminal state. Always report the job ID, run name, and output directory. Include the next check cadence if a follow-up was scheduled; otherwise include the download-status command.
7. Rank hits from <output-root>/<run-name>/results/index.jsonl by binding_confidence descending. Use iptm and min_interaction_pae as tiebreakers. optimization_score is not emitted for this endpoint. Read references/results.md for output layout and metric details.

Command Pattern

# Replace placeholders with concrete absolute paths before running.
# Use a short descriptive run name, for example: protein-screen-<target>-<library>-v1

boltz-api protein:library-screen start \
       --idempotency-key "<run-name>" \
       --input @yaml:///absolute/path/payload.yaml \
       --raw-output --transform id

# Copy the printed job ID into this command, then launch it as a
# long-running/background command via the host agent harness.
boltz-api download-results \
  --id "<job-id-from-start>" --name "<run-name>" \
  --root-dir "/absolute/path/boltz-experiments" \
  --poll-interval-seconds 30

Payload keys are proteins, target — API body field names.

Always Do This

• For structure_template, embed CIF/PDB bytes with @data:///abs/path/target.cif inside the structure.data field. Don't use bare @path (the auto-sniff once sent CIF as plain text into a base64 field and broke the server parser).
• Residue indices are 0-based. epitope_residues and flexible_residues must be subsets of crop_residues.
• Keep payload field names exactly as the API body names shown in references/api.md.
• Use absolute paths for the output root, payload files, and embedded target files. Do not cd into the run directory for follow-up commands; pass the same --root-dir and use absolute paths so later relative paths do not drift.
• Prefer one merged top-level payload via --input @yaml:///absolute/path/payload.yaml or @json:///absolute/path/payload.json. Keep --idempotency-key and --workspace-id top-level; if they also appear inside --input, the top-level flags win.
• Direct object flags still work as overrides, such as --target @yaml:///absolute/path/target.yaml or repeated --protein @json:///absolute/path/protein-1.json entries. Piped YAML / JSON on stdin also works, but it must use API body field names. Never use @file:// or @./.
• Use the same slug as both --idempotency-key and --name.
• In permission-gated agents, keep each Boltz call as a top-level command that starts with boltz-api. Prefer concrete arguments over sh -c, inline environment assignments, aliases, wrapper scripts, loops, or pipelines around the boltz-api invocation unless the user already allowed that exact command form. Use --raw-output --transform id, read the printed ID, then paste that literal ID into the next download-results command.
• Run download-results through the host harness's long-running/background command facility. After it starts, do not manually wait on it or run ad hoc polling loops. Wall-clock time scales roughly with candidate count: under 100 often finishes in a few minutes, 100-1,000 may take several minutes to tens of minutes, and larger screens can take longer or hours depending on inputs and system load. If the host harness provides a managed follow-up/notification mechanism, schedule it to check download-status, notify the user on terminal completion/failure, and stop once terminal. If not, do not claim an automatic next check. --poll-interval-seconds 30 is a reasonable downloader default.
• download-results emits JSONL progress on stderr by default; add --progress-format text --verbose only when you explicitly want human-readable logs.
• Prefer boltz-api --format json download-status --name "<run-name>" --root-dir "/absolute/path/boltz-experiments" for structured local checkpoint state. When the host provides a managed follow-up mechanism, use it for automatic checks with cadence based on candidate count: under 100 -> every 1-2 minutes; 100-1,000 -> every 5 minutes; over 1,000 -> every 15 minutes. Never run a manual poll loop in the current turn.
• If a detached download needs to be restarted, re-run boltz-api download-results with the same --name "<run-name>" and the same --root-dir.

Escape Hatch

• Payload reference: https://api.boltz.bio/docs/api/python/resources/protein/subresources/library_screen/methods/start
• CLI flag names: boltz-api protein:library-screen start --help

Read references/api.md for the proteins list shape and both target variants (structure_template with chain_selection, and no_template with epitope hints). Read references/results.md after download when ranking screened binders or explaining outputs.

Outputs

Rank from results/index.jsonl after download-results; use references/results.md for local file layout and metric meanings.