Proteina Complexa

What it does

When your agent uses it

• Generating de novo protein backbones with hierarchical fold conditioning
• Exploring long-chain backbone generation beyond standard diffusion baselines
• Using NVIDIA Proteina-style flow matching workflows for controllable backbone design
• Comparing flow-based backbone generation against RFdiffusion

Example prompts

• “Proteina-Complexa”
• “/proteina-complexa”

Requirements

• Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

1. 1Start from backbone generation
2. 2Prefer fold-conditioned exploration
3. 3Hand off to sequence design
4. 4Validate and filter

What it can do on your machine

Read from SKILL.md and the folder at commit 8cbdd18. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • git
  • mamba
  • conda
  • pip

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • github.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Proteina Complexa loads about 1.4k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 198 tokens; SKILL.md has 494 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~198

When it runs · the whole SKILL.md, loaded when a task matches

~1.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NoteMentions a .env fileSKILL.md:51

  Create a `.env` file in the repository root:

• NoteMentions a .env fileSKILL.md:53

  cho "DATA_PATH=/path/to/proteina-data" > .env

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from BioTender-max/awesome-bio-agent-skills at commit 8cbdd18, republished under its MIT licence (© BioTender-max). 494 words, ~1,406 tokens.

name

proteina-complexa

description

Proteina-Complexa flow-based protein backbone generation with fold-conditioned sampling guidance. Use this skill when: (1) Generating de novo protein backbones with hierarchical fold conditioning, (2) Exploring long-chain backbone generation beyond standard diffusion baselines, (3) Using NVIDIA Proteina-style flow matching workflows for controllable backbone design, (4) Comparing flow-based backbone generation against RFdiffusion or BoltzGen, (5) Prototyping fold-guided backbone campaigns before sequence design. This skill is based on the public NVIDIA Digital Bio Proteina project and uses "Proteina-Complexa" as the BioClaw-facing skill label. For sequence design after backbone generation, use proteinmpnn or solublempnn. For QC thresholds, use protein-design-qc.

license

MIT

category

design-tools

tags

structure-design, backbone-generation, flow-matching, fold-conditioning

git clone https://github.com/NVIDIA-Digital-Bio/proteina.git
cd proteina
mamba env create -f environment.yaml
conda activate proteina_env
pip install -e .

echo "DATA_PATH=/path/to/proteina-data" > .env

Target goal
  -> Proteina-Complexa backbone generation
  -> ProteinMPNN / SolubleMPNN sequence design
  -> Chai / Boltz / AlphaFold validation
  -> Protein Design QC

© BioTender-max, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/bioclaw_hub/proteina-complexa of BioTender-max/awesome-bio-agent-skills.

• SKILL.md
• README.md
• references/upstream-notes.md

Open the folder on GitHubat commit 8cbdd18