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Boltz Structure And Binding

OpenAIOfficialCreated by BoltzDistributed by OpenAI

  • Skill
  • Tool integration
  • Science and research
  • MIT
  • No issues found

From the author

Predict structures and binding for one defined complex with Boltz. Use when folding a protein, RNA, DNA, or ligand complex, docking one ligand, predicting an interface, or scoring binding. Not for screening libraries or design.
— the description by Boltz

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured workflow for using the Boltz API to perform structural prediction and binding analysis on specific molecular complexes. It covers the entire process from input normalization and cost estimation to job submission and asynchronous result retrieval. It is designed for single-complex analysis rather than high-throughput screening or molecular design.

What it does

  • Normalizes molecular entities including proteins, RNA, DNA, and ligands into the required API format.
  • Configures binding analysis for ligand-protein or protein-protein interactions.
  • Estimates computational costs before job submission.
  • Manages asynchronous job execution and background result downloading.
  • Summarizes key metrics such as binding confidence and optimization scores from output files.

When to use it

  • When you need to fold a specific protein, RNA, DNA, or ligand complex.
  • When you need to predict the interface or binding affinity of a defined complex.
  • When you need to dock a single ligand into a protein structure.
  • When you have a specific molecular system and require structural confidence metrics.

Advantages

  • Ensures correct payload formatting to avoid common API validation errors.
  • Provides a robust, non-blocking workflow for handling long-running structural predictions.
  • Standardizes the handling of complex molecular inputs and binding configurations.
  • Facilitates clear reporting of structural and binding confidence metrics.

Usage examples

“Predict the structure of a protein-ligand complex with protein chain A and ligand chain B.”
The agent will normalize the entities, request a cost estimate, submit the job, and initiate a background download of the resulting CIF structure and metrics.
“What is the binding confidence for this protein-protein complex?”
The agent will configure the binding block for protein-protein interaction, run the prediction, and extract the binding_confidence metric from the results.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/openai/boltz-structure-and-binding/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip boltz-structure-and-binding.zip -d .agents/skills

Documentation by Boltz

Workflow

If boltz-api is missing from PATH, use boltz-cli-setup for install/update guidance before retrying. If a command reports missing or expired authentication, use boltz-cli-setup to start boltz-api auth login --device-code before retrying; do not ask permission first. If the agent host sandbox blocks boltz-api install/auth/API calls, use boltz-cli-setup to request the host sandbox bypass/escalation needed for user-wide CLI install, browser login, credential storage, temp files, or API access before retrying.

Use this skill for one defined complex, not a library workflow.

  1. Normalize the inputs into entities. Each entity is {type, chain_ids, value} — note plural chain_ids (an array, even for one chain) and the field is value, not sequence:

    {"entities": [{"type": "protein", "chain_ids": ["A"], "value": "MKTAYIAKQRQISFVKSHFSRQ"}]}

    type is one of protein | rna | dna | ligand_smiles | ligand_ccd. Chain IDs go in entity order (A, B, C, …) unless the user specifies otherwise. Read references/api.md for per-type field variants (cyclic, modifications, ligand CCD codes, etc.) before authoring your first payload — agent guesses like sequence: or chain_id: "A" (singular) fail with unclear 400 errors.

  2. If the user wants binding metrics, add a flat binding block with an explicit type field. For ligand-protein binding use:

    binding:
      type: ligand_protein_binding
      binder_chain_id: B

    For protein-protein binding use:

    binding:
      type: protein_protein_binding
      binder_chain_ids: [B]

    Do not nest the variant name under binding (for example, no binding.ligand_protein_binding object).

  3. Supported optional features include constraints, bonds, modifications, model_options, and binding metrics; only add them if the user asks. Read references/api.md for exact shapes and examples.

  4. Author the payload YAML or JSON, run estimate-cost, show the USD cost, wait for explicit confirmation.

  5. start to submit (synchronous). Capture the ID.

  6. Launch download-results with the agent runtime's background/non-blocking command facility so polling + download continue without blocking the agent session. In Claude Code, use Bash with run_in_background: true. In Codex, run download-results as a foreground shell command with yield_time_ms: 1000; if Codex returns a session_id, keep it for optional same-thread polling, but treat download-status plus the run directory as the durable source of truth. In Codex app/desktop runtimes that expose same-thread heartbeat automations, create a heartbeat that checks download-status periodically and posts a concise completion or failure update when the download reaches a terminal state. After launching the downloader, always report the job ID, run name, and output directory. Include the next check cadence if the heartbeat was created; otherwise include the download-status command.

Command Pattern

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

# 1. estimate
boltz-api predictions:structure-and-binding estimate-cost \
  --model boltz-2.1 \
  --input @yaml:///absolute/path/payload.yaml

# 2. confirm with user, then submit
boltz-api predictions:structure-and-binding start \
       --model boltz-2.1 \
       --idempotency-key "<run-name>" \
       --input @yaml:///absolute/path/payload.yaml \
       --raw-output --transform id

# 3. Copy the printed job ID into this command, then launch it in the agent
# runtime's background/non-blocking mode.
# Claude Code: Bash with run_in_background=true.
# Codex: foreground shell command with yield_time_ms=1000; keep the returned session_id if one is provided.
# Do not append "&" or use nohup in Codex.
boltz-api download-results \
  --id "<job-id-from-start>" --name "<run-name>" \
  --root-dir "/absolute/path/boltz-experiments" \
  --poll-interval-seconds 10
# -> /absolute/path/boltz-experiments/<run-name>/outputs/archive.tar.gz, .boltz-run.json

Always Do This

  • Keep payload field names exactly as the API body names shown in references/api.md; then pass the merged payload with --input @yaml:///absolute/path/payload.yaml or @json:///absolute/path/payload.json. Never use @./payload.yaml or @file:// for object-typed payloads.

  • Use absolute paths for the output root, payload files, and embedded structure 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.

  • Residue indices are 0-based wherever the payload asks for residue positions (constraints, modifications, contact tokens).

  • For CIF/PDB bytes embedded in --target / structure.data, use @data:///absolute/path/file.cif — it detects binary and base64-encodes. Don't use bare @path for binary data.

  • Use the same slug as both --idempotency-key at submit time and --name at download time so re-runs are idempotent and resume from .boltz-run.json.

  • In permission-gated agents such as Claude Code, 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.

  • Prefer the agent runtime's background/non-blocking command mode for download-results. In Codex specifically, keep download-results in the foreground and set the shell tool yield to 1000 ms; Codex will return a session_id if the command is still running. Do not append & or use nohup in Codex because the tool runner may clean up shell-backgrounded descendants before .boltz-run.json is fully written.

  • After the background/session starts, do not manually wait on it or run ad hoc polling loops. download-results emits JSONL progress on stderr by default; add --progress-format text --verbose only when you explicitly want human-readable logs.

  • In Codex app/desktop runtimes with same-thread heartbeat automation support, schedule a heartbeat after launching download-results. The heartbeat should run boltz-api --format json download-status --name "<run-name>" --root-dir "/absolute/path/boltz-experiments" on a sensible cadence, post only material status changes or terminal completion/failure, and stop once terminal. Poll the saved session_id with an empty write_stdin only for interactive, user-requested progress checks. Do not loop retrieve yourself.

  • If the current host has no heartbeat automation support, do not claim an automatic next check. Report the job ID, run name, output directory, and the command needed to check download-status.

  • If detached download needs to be restarted, re-run boltz-api download-results with the same --name "<run-name>" and the same --root-dir.

  • Poll interval: keep --poll-interval-seconds 10 for SAB — predictions usually finish in under a few minutes.

  • Cost: there is no published per-unit rate to cite for SAB — run estimate-cost and state only the figure it returns. Don't estimate or comment on cost.

Escape Hatch

For anything not covered in references/api.md:

Read references/api.md for entity shapes, binding variants, bonds, constraints, model options, and input examples. Read references/results.md when summarizing downloaded outputs, metrics, or validation quirks.

Outputs

Summarize metrics.json and point the user at the downloaded CIF path. Read references/results.md for the local layout, nested metrics, binding metric variants, and SAB validation quirks.

SAB 400 validation quirk

If the server rejects a payload with only {"code":"VALIDATION_ERROR","message":"Request validation failed"}, inspect entities, binding, and constraints; read references/results.md for details.

Files

SKILL.md

Workflow

If boltz-api is missing from PATH, use boltz-cli-setup for install/update guidance before retrying. If a command reports missing or expired authentication, use boltz-cli-setup to start boltz-api auth login --device-code before retrying; do not ask permission first. If the agent host sandbox blocks boltz-api install/auth/API calls, use boltz-cli-setup to request the host sandbox bypass/escalation needed for user-wide CLI install, browser login, credential storage, temp files, or API access before retrying.

Use this skill for one defined complex, not a library workflow.

  1. Normalize the inputs into entities. Each entity is {type, chain_ids, value} — note plural chain_ids (an array, even for one chain) and the field is value, not sequence:

    {"entities": [{"type": "protein", "chain_ids": ["A"], "value": "MKTAYIAKQRQISFVKSHFSRQ"}]}

    type is one of protein | rna | dna | ligand_smiles | ligand_ccd. Chain IDs go in entity order (A, B, C, …) unless the user specifies otherwise. Read references/api.md for per-type field variants (cyclic, modifications, ligand CCD codes, etc.) before authoring your first payload — agent guesses like sequence: or chain_id: "A" (singular) fail with unclear 400 errors.

  2. If the user wants binding metrics, add a flat binding block with an explicit type field. For ligand-protein binding use:

    binding:
      type: ligand_protein_binding
      binder_chain_id: B

    For protein-protein binding use:

    binding:
      type: protein_protein_binding
      binder_chain_ids: [B]

    Do not nest the variant name under binding (for example, no binding.ligand_protein_binding object).

  3. Supported optional features include constraints, bonds, modifications, model_options, and binding metrics; only add them if the user asks. Read references/api.md for exact shapes and examples.

  4. Author the payload YAML or JSON, run estimate-cost, show the USD cost, wait for explicit confirmation.

  5. start to submit (synchronous). Capture the ID.

  6. Launch download-results with the agent runtime's background/non-blocking command facility so polling + download continue without blocking the agent session. In Claude Code, use Bash with run_in_background: true. In Codex, run download-results as a foreground shell command with yield_time_ms: 1000; if Codex returns a session_id, keep it for optional same-thread polling, but treat download-status plus the run directory as the durable source of truth. In Codex app/desktop runtimes that expose same-thread heartbeat automations, create a heartbeat that checks download-status periodically and posts a concise completion or failure update when the download reaches a terminal state. After launching the downloader, always report the job ID, run name, and output directory. Include the next check cadence if the heartbeat was created; otherwise include the download-status command.

Command Pattern

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

# 1. estimate
boltz-api predictions:structure-and-binding estimate-cost \
  --model boltz-2.1 \
  --input @yaml:///absolute/path/payload.yaml

# 2. confirm with user, then submit
boltz-api predictions:structure-and-binding start \
       --model boltz-2.1 \
       --idempotency-key "<run-name>" \
       --input @yaml:///absolute/path/payload.yaml \
       --raw-output --transform id

# 3. Copy the printed job ID into this command, then launch it in the agent
# runtime's background/non-blocking mode.
# Claude Code: Bash with run_in_background=true.
# Codex: foreground shell command with yield_time_ms=1000; keep the returned session_id if one is provided.
# Do not append "&" or use nohup in Codex.
boltz-api download-results \
  --id "<job-id-from-start>" --name "<run-name>" \
  --root-dir "/absolute/path/boltz-experiments" \
  --poll-interval-seconds 10
# -> /absolute/path/boltz-experiments/<run-name>/outputs/archive.tar.gz, .boltz-run.json

Always Do This

  • Keep payload field names exactly as the API body names shown in references/api.md; then pass the merged payload with --input @yaml:///absolute/path/payload.yaml or @json:///absolute/path/payload.json. Never use @./payload.yaml or @file:// for object-typed payloads.

  • Use absolute paths for the output root, payload files, and embedded structure 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.

  • Residue indices are 0-based wherever the payload asks for residue positions (constraints, modifications, contact tokens).

  • For CIF/PDB bytes embedded in --target / structure.data, use @data:///absolute/path/file.cif — it detects binary and base64-encodes. Don't use bare @path for binary data.

  • Use the same slug as both --idempotency-key at submit time and --name at download time so re-runs are idempotent and resume from .boltz-run.json.

  • In permission-gated agents such as Claude Code, 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.

  • Prefer the agent runtime's background/non-blocking command mode for download-results. In Codex specifically, keep download-results in the foreground and set the shell tool yield to 1000 ms; Codex will return a session_id if the command is still running. Do not append & or use nohup in Codex because the tool runner may clean up shell-backgrounded descendants before .boltz-run.json is fully written.

  • After the background/session starts, do not manually wait on it or run ad hoc polling loops. download-results emits JSONL progress on stderr by default; add --progress-format text --verbose only when you explicitly want human-readable logs.

  • In Codex app/desktop runtimes with same-thread heartbeat automation support, schedule a heartbeat after launching download-results. The heartbeat should run boltz-api --format json download-status --name "<run-name>" --root-dir "/absolute/path/boltz-experiments" on a sensible cadence, post only material status changes or terminal completion/failure, and stop once terminal. Poll the saved session_id with an empty write_stdin only for interactive, user-requested progress checks. Do not loop retrieve yourself.

  • If the current host has no heartbeat automation support, do not claim an automatic next check. Report the job ID, run name, output directory, and the command needed to check download-status.

  • If detached download needs to be restarted, re-run boltz-api download-results with the same --name "<run-name>" and the same --root-dir.

  • Poll interval: keep --poll-interval-seconds 10 for SAB — predictions usually finish in under a few minutes.

  • Cost: there is no published per-unit rate to cite for SAB — run estimate-cost and state only the figure it returns. Don't estimate or comment on cost.

Escape Hatch

For anything not covered in references/api.md:

Read references/api.md for entity shapes, binding variants, bonds, constraints, model options, and input examples. Read references/results.md when summarizing downloaded outputs, metrics, or validation quirks.

Outputs

Summarize metrics.json and point the user at the downloaded CIF path. Read references/results.md for the local layout, nested metrics, binding metric variants, and SAB validation quirks.

SAB 400 validation quirk

If the server rejects a payload with only {"code":"VALIDATION_ERROR","message":"Request validation failed"}, inspect entities, binding, and constraints; read references/results.md for details.

Requirements and compatibility

Written for: OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

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Attribution and licence

Created by
Boltz
Publisher
OpenAI (Official)
Distributed by
OpenAI
Source
openai/plugins · plugins/boltz-api-cli/skills/boltz-structure-and-binding · commit d420d13
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from plugins/boltz-api-cli/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download boltz-structure-and-binding.zip