Menu

Individual skill

setup-apnovo-remote-tool

0upvotes

Set up, launch, validate, and troubleshoot the AlphaProtein Novo (de novo enzyme design) ToolUniverse remote tool. Use when deploying or auditing this implementation.

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

Read pinned source

Source commit 5598a9fc97e32964fe9b703818e7d0747142f179

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,779
Repository last updated
Nov 8, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Set up AlphaProtein Novo as a remote tool

> Validation status (2026-10-16): **`verified`.** The acceptance suite has now run twice, 12/12 requests answered each time with `peak_reserved_gib` 2.0 on every one; see `provider.toml`'s `verified_on`. Earlier status (2026-10-06): all five setup steps pass. On the NVIDIA GB10 (aarch64, cc 12.1, driver 580.173.02): `tu remote setup apnovo` reports preflight OK, environment present, kit at the pinned commit, weights 1/1 at their pins, and `smoke: OK — one prediction in 69s, peak reserved 2.0 GiB`, which agrees with the manifest's independently measured budget. The weights refusal was tested in both directions. Residency is **5.3x** at the published 1000 denoising steps (193.1 s for the design that pays the XLA compile, 36.6 s for the one that reuses it) and far larger at 50 steps (158.5 s and 1.99 s), where compilation rather than compute dominates — plan with the figure at your own step count. Folding and resequencing are deliberately not part of this provider. What has been established on
> the NVIDIA GB10 (aarch64, cc 12.1, driver 580.173.02) is the environment and
> the no-weights path: the 72-package lock installs natively, `alphafold3`'s C++
> extension builds from source, the pinned stack reports
> `jax.default_backend() == "gpu"` on `CudaDevice(id=0)` "NVIDIA GB10"
> cc 12.1, and a design manifest validates and its motif spec parses with no
> weights and no GPU. The generator weights have been fetched and their sha256
> recorded. **Not** established: the residency gain, the acceptance suite, and
> scientific quality. Folding and resequencing are deliberately not part of this
> provider — see the provider README for why. Keep this deployment private.

**Read `src/tooluniverse/remote/apnovo/README.md` before deploying.** This
Back to top