Protein Engineering Hypothesis

Organization

ai4protein

protein_engineering_hypothesis

Evidence-bounded hypothesis and experiment planning for protein engineering. Use when the user asks what to mutate next, how to prioritize variants, how to falsify a mechanism, or how to design a directed-evolution round. Do NOT invent wet-lab results; chain VenusFactory tools for computational evidence and label model scores as hypotheses.

Overview

Publisher	ai4protein
Repository	`VenusFactory2`
Skill name	`protein_engineering_hypothesis`
Stars	255
Forks	37
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by ai4protein on GitHub. Read the source before you install it.

Installation

Install the Protein Engineering Hypothesis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/ai4protein/VenusFactory2/tree/main/src/agent/skills/protein_engineering_hypothesis
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/ai4protein/VenusFactory2/tree/main/src/agent/skills/protein_engineering_hypothesis

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ai4protein/VenusFactory2.git /tmp/VenusFactory2
mkdir -p .claude/skills
cp -r /tmp/VenusFactory2/src/agent/skills/protein_engineering_hypothesis .claude/skills/protein_engineering_hypothesis

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Protein Engineering Hypothesis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Protein Engineering Hypothesis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Protein Engineering Hypothesis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Protein Engineering Hypothesis

Overview

Instruction-only skill: structure the scientific argument, then point MLS at concrete hub tools. Inspired by scientific-agent-skills hypothesis-generation, adapted to VenusFactory protein tools.

VenusFactory execution

Load this skill.
Produce a short plan with: Observation → Hypothesis → Computational test → Wet-lab falsifier.
Execute tests via other skills/tools (do not reimplement).

Recommended evidence chain

Question	Skills / tools
What is known about the protein?	`uniprot_database`, `interpro_domain_annotation`, `pubmed`
Where is it expressed?	`hpa_expression_context`
Structure confidence?	`protein_structure_pipeline` / `alphafold_database`
Which mutations look beneficial?	`zero_shot_mutation_workflow`
Redesign backbone-constrained seq?	`proteinmpnn_design_workflow`
Kinetics / EC?	`brenda_database`
Partners / pathways?	`string_database`, `kegg_database`
Train a custom head?	`venus_finetune_workflow`

Output template (for CB/MLS)

markdown
### Observation
...
### Hypothesis (falsifiable)
...
### Computational tests (ordered)
1. tool/skill … success = …
### Predicted outcome
...
### Wet-lab falsifier (suggested, not executed here)
...
### Risks / confounders
- Model score ≠ experimental activity

Rules

Never present zero-shot / PLM ranks as measured ΔΔG or activity.
Prefer protecting catalytic residues (interpro + literature) before design.
End computational rounds with at least one figure when numeric tables exist.

When NOT to use

User only wants a single tool call with no scientific framing — call that tool's skill directly.

Frequently asked questions

What does the Protein Engineering Hypothesis AI skill do?

Why use Protein Engineering Hypothesis on TypingMind?

Because you install it once and use it with any model. Protein Engineering Hypothesis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Protein Engineering Hypothesis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ai4protein/VenusFactory2/tree/main/src/agent/skills/protein_engineering_hypothesis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Protein Engineering Hypothesis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Protein Engineering Hypothesis?

As many as you like. As long as a model supports skills, you can use Protein Engineering Hypothesis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Protein Engineering Hypothesis AI skill free?

Yes. It is published on GitHub by ai4protein under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Protein Engineering Hypothesis

Overview

VenusFactory execution

Recommended evidence chain

Output template (for CB/MLS)

Rules

When NOT to use

Frequently asked questions

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