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setup-opendde-remote-tool

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Set up, launch, validate, and troubleshoot the OpenDDE ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.

skills/setup-opendde-remote-tool/SKILL.md

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# Set up OpenDDE as a remote tool

> Validation status (2026-10-02): OpenDDE 1.1.1 ran on the NVIDIA GB10 (aarch64, cc 12.1, driver 580.173.02) with the optimization kit OFF, torch 2.7.1+cu128 and the triangle kernels resolved by upstream to torch. This provider is UNTESTED, not verified. Established by running it: all five `tu remote setup` steps (smoke: one 35-residue fold, five samples, pLDDT about 93.5, peak reserved 3.12 GiB), and a 100/200/400-residue ladder in two separate held workers with identical peaks of 3.69 / 6.85 / 22.55 GiB. NOT established: four consecutive identical requests, the mixed sequence, residency gains, the ceiling refusals, the hostile-environment launcher test, and the example below through the live MCP endpoint, because the host's memory guard refused to start a worker (about 5 GiB free, co-tenants holding the rest). Wall times seen were on a heavily contended card and are not measurements. Public publication, cross-user isolation, concurrency, recovery and structural accuracy are untested; keep this deployment private.

## What OpenDDE is, and what one request means

OpenDDE (Aureka AI Research, Apache 2.0, PyPI `opendde` 1.1.1, model `opendde_v1`, 655.8 M parameters, one general-purpose checkpoint `opendde.pt`) is an AlphaFold3-class all-atom co-folding model. It folds a complex of protein, DNA and RNA chains, ligands and ions into diffusion-sampled mmCIF structures and scores every sample (pLDDT, pTM, ipTM, PAE, a ranking score). Its code descends from Protenix's, and so does its input dialect: an AlphaFold-Server style job whose entities are `proteinChain`, `dnaSequence`, `rnaSequence`, `ligand` and `ion`, each with a `count`.

**One request is one complex folded for one seed**: up to 5 diffusion samples (`num_diffusion_samples`), each separately scored, through `num_recycles` Pairformer cycles (default 10) and `num_diffusion_steps` steps per sample (default 200). Rank the samples on `ranking_score`.

Three deployment decisions are not oversights:

- **No MSA search, no templates.** `opendde pred` posts the query to an MSA web service before folding, and OpenDDE accepts alignments only as file paths on the host. Neither is acceptable on a remote caller's say-so, so every request is folded **single-sequence** and the reply says so (`use_msa: false`). Single-sequence OpenDDE is materially less accurate than MSA-fed OpenDDE.
- **Ligands are SMILES or `CCD_<id>`.** Upstream's `FILE_<path>` form reads a file off the host and is refused.
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