Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
De novo antibody and nanobody (VHH) design with Germinal. An agent skill from adaptyvbio/protein-design-skills.
Install Germinal
$ npx skills add adaptyvbio/protein-design-skills --skill germinal -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install adaptyvbio/protein-design-skills germinal --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/germinal .claude/skills/germinal && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "germinal" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal into .claude/skills/germinal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "germinal", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinalType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add adaptyvbio/protein-design-skills --skill germinal -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install adaptyvbio/protein-design-skills germinal --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/germinal .agents/skills/germinal && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "germinal" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal into .agents/skills/germinal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "germinal", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add adaptyvbio/protein-design-skills --skill germinal -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install adaptyvbio/protein-design-skills germinal --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/germinal .cursor/skills/germinal && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "germinal" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal into .cursor/skills/germinal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "germinal", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/adaptyvbio/protein-design-skills.git --path skills/germinal--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add adaptyvbio/protein-design-skills --skill germinal -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install adaptyvbio/protein-design-skills germinal --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/germinal .gemini/skills/germinal && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "germinal" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal into .gemini/skills/germinal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "germinal", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install adaptyvbio/protein-design-skills germinalInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add adaptyvbio/protein-design-skills --skill germinal -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/germinal .github/skills/germinal && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "germinal" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal into .github/skills/germinal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "germinal", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add adaptyvbio/protein-design-skills --skill germinal -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install adaptyvbio/protein-design-skills germinal --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/germinal .opencode/skills/germinal && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "germinal" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal into .opencode/skills/germinal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "germinal", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
germinal- GitHub stars
- 163
- Used in
- 2 other repos
- Token cost
- ~739 tokens
- SKILL.md length
- 206 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- MIT
At a glance
De novo antibody and nanobody (VHH) design with Germinal. An agent skill from adaptyvbio/protein-design-skills.
- Designing epitope-targeted nanobodies
- SKILL.md covers Prerequisites, How to run, Key parameters and Target YAML, plus 3 more sections
- Calls git and uv; reaches github.com
- Needing CDR design on a fixed framework
What it does
Germinal is an agent skill from adaptyvbio/protein-design-skills. De novo antibody and nanobody (VHH) design with Germinal. Use this skill when: (1) Designing epitope-targeted nanobodies or scFvs, (2) Needing CDR design on a fixed framework, (3) Working on antibody-format binders rather than miniproteins. For miniprotein binders, use binder-design (BoltzGen, BindCraft, RFdiffusion, Mosaic). For structure validation, use boltz or chai.
Its SKILL.md is about 740 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science. The repository describes itself as: Claude Code skills for protein design. The licence is MIT.
When your agent uses it
- Designing epitope-targeted nanobodies
- Needing CDR design on a fixed framework
- Working on antibody-format binders rather than miniproteins
Example prompts
- “/germinal”
What it can do on your machine
Read from SKILL.md and the folder at commit 59dd633. 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:
gituv
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
Germinal loads about 739 tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 206 words of instructions outside code blocks.
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
Auto-check passed
The automated check found no risky patterns in SKILL.md.
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 adaptyvbio/protein-design-skills at commit 59dd633, republished under its MIT licence (© adaptyvbio). 206 words, ~739 tokens.
Download SKILL.mdSave it as
.claude/skills/germinal/SKILL.md (or your agent's skills folder).- name
- germinal
- description
- De novo antibody and nanobody (VHH) design with Germinal. Use this skill when: (1) Designing epitope-targeted nanobodies or scFvs, (2) Needing CDR design on a fixed framework, (3) Working on antibody-format binders rather than miniproteins. For miniprotein binders, use binder-design (BoltzGen, BindCraft, RFdiffusion, Mosaic). For structure validation, use boltz or chai.
- license
- MIT
- category
- design-tools
- tags
- antibody, nanobody, vhh, scfv, binder
- biomodals_script
- modal_germinal.py
Germinal Antibody and Nanobody Design
Germinal is an open pipeline for epitope-targeted de novo antibody and nanobody design. It hallucinates CDRs on a fixed framework, designs sequences with AbMPNN, and cofolds with a structure predictor (it downloads AlphaFold-Multimer params). Runnable through biomodals.
The biomodals author notes Germinal is finicky and suggests BoltzGen for general binder design; treat Germinal as the antibody-format option, not a default.
Prerequisites
| Requirement | Value |
|---|---|
| Runner | Modal (biomodals) |
| GPU | H100 (default; GPU env var) |
| Setup | See Getting started |
How to run
git clone https://github.com/hgbrian/biomodals && cd biomodals
uv run --with modal --with PyYAML modal run modal_germinal.py \
--target-yaml target_example.yaml \
--max-trajectories 1 \
--max-passing-designs 1Key parameters
| Parameter | Default | Description |
|---|---|---|
--target-yaml | required | Target config (target_name, target_pdb_path, target_chain, binder_chain, target_hotspots, length) |
--run-type | vhh | vhh (nanobody) or scfv |
--max-trajectories | 100 | Trajectories to run |
--max-passing-designs | 10 | Stop after this many passing designs |
--out-dir | ./out/germinal | Output directory |
Target YAML
target_name: PDL1
target_pdb_path: target.pdb
target_chain: A
binder_chain: B
target_hotspots: "45,67,89"
length: 120Decision tree
Antibody-format binder?
│
├─ Nanobody / VHH → germinal (run-type vhh) or mber
├─ scFv → germinal (run-type scfv)
└─ Miniprotein (not antibody) → binder-design (boltzgen, bindcraft, mosaic)For VHH nanobodies, biomodals also has modal_mber.py (mBER) and modal_iggm.py
(IgGM) as alternatives.
Cost
Adaptyv's own tests of these models showed Germinal costing about $1.60 per accepted design, averaged across 7 targets.
Troubleshooting
| Issue | Cause | Fix |
|---|---|---|
| Pipeline fails early | Missing PyYAML | Add --with PyYAML to the invocation |
| No passing designs | Hard epitope or low budget | Raise --max-trajectories |
| OOM | Large target | Use the default H100 or trim the target |
Next: Validate with boltz or chai, rank with ipsae, filter with protein-qc.
© adaptyvbio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/germinal of adaptyvbio/protein-design-skills.
Open the folder on GitHubat commit 59dd633
Used in 2 other repositories
We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in adaptyvbio/protein-design-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Germinal next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Germinal this skilladaptyvbio/protein-design-skills | 163 | 2 repos | ~739 | Automated safety check: Pass | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 46k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Read arXiv Paperkarpathy/nanochat | 58k | 2 repos | ~494 | Automated safety check: Pass | MIT | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT |
Similar skills
GitHub Deep Research
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
Nature Paper Card
Yuan1z0825/nature-skills
Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.
Read arXiv Paper
karpathy/nanochat
Fetches the TeX source of an arXiv paper from its URL, reads it and writes a markdown summary tied to the nanochat project.
Content Research Writer
weapp-tailwindcss/weapp-tailwindcss
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.
Peer Review
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
More from adaptyvbio/protein-design-skills
All 24 skills in this repoAlphafold
adaptyvbio/protein-design-skills
Validate protein designs using AlphaFold2 structure prediction.
Bindcraft
adaptyvbio/protein-design-skills
End-to-end binder design using BindCraft hallucination. An agent skill from adaptyvbio/protein-design-skills.
Boltzgen
adaptyvbio/protein-design-skills
All-atom protein design using BoltzGen diffusion model. An agent skill from adaptyvbio/protein-design-skills.
Chai
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Structure prediction using Chai-1, a foundation model for molecular structure.
Protein Design Workflow
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End-to-end guidance for protein design pipelines. An agent skill from adaptyvbio/protein-design-skills.
Protein Qc
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Quality control metrics and filtering thresholds for protein design.
Related
Categories
Questions about Germinal
What does Germinal do?
De novo antibody and nanobody (VHH) design with Germinal. An agent skill from adaptyvbio/protein-design-skills. Germinal is an agent skill from adaptyvbio/protein-design-skills. De novo antibody and nanobody (VHH) design with Germinal.
When should I use Germinal?
Germinal fits situations like: designing epitope-targeted nanobodies; needing CDR design on a fixed framework; working on antibody-format binders rather than miniproteins.
How do I install Germinal in Claude Code?
Run `npx skills add adaptyvbio/protein-design-skills --skill germinal -a claude-code`. Or copy the skill folder (skills/germinal in adaptyvbio/protein-design-skills) into .claude/skills/germinal in your project. Claude Code loads it when a task matches its description.
How do I install Germinal in Codex?
Run `npx skills add adaptyvbio/protein-design-skills --skill germinal -a codex`. Or copy the skill folder (skills/germinal in adaptyvbio/protein-design-skills) into .agents/skills/germinal in your project. Codex loads it when a task matches its description.
Can I use Germinal in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add adaptyvbio/protein-design-skills --skill germinal -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/germinal, .gemini/skills/germinal, .github/skills/germinal and .opencode/skills/germinal in your project.
What does Germinal need to run?
Going by SKILL.md and its folder, Germinal needs the command-line tools its instructions call (git and uv).
Does Germinal access the network?
SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Germinal safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Germinal use?
Germinal is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Germinal use?
About 739 tokens (SKILL.md is roughly 3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Germinal?
Skills that share tags, products or a category with Germinal: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Germinal?
adaptyvbio (a GitHub organization) maintains it in adaptyvbio/protein-design-skills, which has 163 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on June 11, 2026.
Source: adaptyvbio/protein-design-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.