complexa-sweep SKILL.md skillA
complexa-sweep from nvidia/skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add nvidia/skills/complexa-sweep@git:20261021.69abc15Pins git:20261021.69abc15 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- nvidia/skills
- Path
skills/bionemo-complexa-sweep/SKILL.md- Versions recorded
- 1
- Latest version
- git:20261021.69abc15, committed Oct 21, 2026
- Size
- 16,943 bytes
- Repository stars
- 3,871
- License
- Apache-2.0
Agent runbook for Proteina-Complexa parameter sweeps through the separately installed first-party CLI and config generator. Use for cartesian-product hyperparameter scans, sweeper YAML authoring, configuration comparisons, ablations, tuning, success-rate ranking, or Pareto searches over quality and wall-clock cost. Do not use for a single existing-job launch or SLURM submission template. SKILL.md performs the orchestration; bundled executables only inspect local readiness and write a run…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# complexa-sweep
Run cartesian-product parameter sweeps over Proteina-Complexa design pipelines. Pick or author a sweeper YAML in `configs/sweeps/`, expand it to N inference configs with `script_utils/generate_inference_configs.py`, loop `complexa design` over those configs, then aggregate per-config success metrics into a ranked summary CSV plus a manifest.
> **Important:** The `complexa design` CLI does **NOT** accept `--sweeper` directly. Sweeps are driven by `script_utils/generate_inference_configs.py`, which writes one `configs/inference_configs/inf_{idx}_{run_name}.yaml` per sweep combination. You then loop `complexa design` over those generated configs.
## Instructions
Sweeper authoring, Cartesian enumeration, cost estimates, and analysis of supplied
CSVs need only the relevant configs and data. Complete those artifacts without
setting up inference. Read the relevant axis section in
[sweep_axes.md](references/sweep_axes.md), then check the matching keys in the
selected source config for current defaults. Summary CSVs with supplied counts
and objective columns do not require the full inference or metric guides.
For a partial snapshot,
…Read the whole file at its exact version.
How to install
mdr add nvidia/skills/complexa-sweep@sha256:99da79a2992b661dThe line at the top of this page pins the label git:20261021.69abc15, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_ljq7fny5rbm7gzs7)
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Versions
The registry has recorded 1 version of this file, committed on Oct 21, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (16943 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
nvidia/skills · 3,871 stars · license Apache-2.0 · pushed 2026-11-05 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_ljq7fny5rbm7gzs7 GET https://markdownregistry.com/api/v1/resolve?ref=nvidia/skills/complexa-sweep GET https://markdownregistry.com/api/v1/blob/99da79a2992b661de82308e1e77bcb5501af4c069362f32bcad41ebf7ddf6e68
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.