Agent skill

Adaptyv

by davila7 in davila7/claude-code-templates

Cloud laboratory platform for automated protein testing and validation.

MITAuto-check: notesResearch & Science

Install Adaptyv

skills CLI
$ npx skills add davila7/claude-code-templates --skill adaptyv -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates adaptyv --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/scientific/adaptyv .claude/skills/adaptyv && rm -rf skills-src

Use ~/.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/

Facts

Skill name
adaptyv
GitHub stars
32k
Used in
9 other repos
Token cost
~923 tokens
SKILL.md length
268 words
Files
5
Skills in repo
478
Repo updated
First seen
Licence
MIT

At a glance

Cloud laboratory platform for automated protein testing and validation.

  • Works in 3 steps: Contact support@adaptyvbio.com to… → Receive your API access token → Set environment variable
  • Designing proteins and needing experimental validation including binding assays
  • SKILL.md covers Quick Start, Available Experiment Types, Protein Sequence Optimization and API Reference, plus 2 more sections
  • Calls uv; reaches kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws; needs ADAPTYV_API_KEY

What it does

Adaptyv is an agent skill from davila7/claude-code-templates. Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows…

Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `reference/api_reference.md`, `reference/examples.md` and `reference/experiments.md`).

It sits in Research & Science, covering Protein structure and design. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • Designing proteins and needing experimental validation including binding assays
  • Expression testing
  • Thermostability measurements
  • Enzyme activity assays

Example prompts

  • “/adaptyv”

Requirements

  • Python 3
  • A credential in ADAPTYV_API_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Contact support@adaptyvbio.com to request API access (platform is in alpha/beta)
  2. Receive your API access token
  3. Set environment variable

What it can do on your machine

Read from SKILL.md and the folder at commit 46b4d8b. 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:

    • uv

    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:

    • kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ADAPTYV_API_KEY

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

Context cost

Adaptyv loads about 923 tokens when it runs. Until then it costs about 137 tokens; SKILL.md has 268 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~137
When it runs · the whole SKILL.md, loaded when a task matches
~923

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:24
    Or create a `.env` file:

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 davila7/claude-code-templates at commit 46b4d8b, republished under its MIT licence (© davila7). 268 words, ~923 tokens.

Download SKILL.mdSave it as .claude/skills/adaptyv/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
adaptyv
description
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

Adaptyv

Adaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein sequences via API or web interface and receive experimental results in approximately 21 days.

Quick Start

Authentication Setup

Adaptyv requires API authentication. Set up your credentials:

  1. Contact support@adaptyvbio.com to request API access (platform is in alpha/beta)
  2. Receive your API access token
  3. Set environment variable:
bash
export ADAPTYV_API_KEY="your_api_key_here"

Or create a .env file:

ADAPTYV_API_KEY=your_api_key_here
Installation

Install the required package using uv:

bash
uv pip install requests python-dotenv
Basic Usage

Submit protein sequences for testing:

python
import os
import requests
from dotenv import load_dotenv

load_dotenv()

api_key = os.getenv("ADAPTYV_API_KEY")
base_url = "https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

# Submit experiment
response = requests.post(
    f"{base_url}/experiments",
    headers=headers,
    json={
        "sequences": ">protein1\nMKVLWALLGLLGAA...",
        "experiment_type": "binding",
        "webhook_url": "https://your-webhook.com/callback"
    }
)

experiment_id = response.json()["experiment_id"]

Available Experiment Types

Adaptyv supports multiple assay types:

  • Binding assays - Test protein-target interactions using biolayer interferometry
  • Expression testing - Measure protein expression levels
  • Thermostability - Characterize protein thermal stability
  • Enzyme activity - Assess enzymatic function

See reference/experiments.md for detailed information on each experiment type and workflows.

Protein Sequence Optimization

Before submitting sequences, optimize them for better expression and stability:

Common issues to address:

  • Unpaired cysteines that create unwanted disulfides
  • Excessive hydrophobic regions causing aggregation
  • Poor solubility predictions

Recommended tools:

  • NetSolP / SoluProt - Initial solubility filtering
  • SolubleMPNN - Sequence redesign for improved solubility
  • ESM - Sequence likelihood scoring
  • ipTM - Interface stability assessment
  • pSAE - Hydrophobic exposure quantification

See reference/protein_optimization.md for detailed optimization workflows and tool usage.

API Reference

For complete API documentation including all endpoints, request/response formats, and authentication details, see reference/api_reference.md.

Examples

For concrete code examples covering common use cases (experiment submission, status tracking, result retrieval, batch processing), see reference/examples.md.

Important Notes

  • Platform is currently in alpha/beta phase with features subject to change
  • Not all platform features are available via API yet
  • Results typically delivered in ~21 days
  • Contact support@adaptyvbio.com for access requests or questions
  • Suitable for high-throughput AI-driven protein design workflows

© davila7, 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 4 other files in cli-tool/components/skills/scientific/adaptyv of davila7/claude-code-templates.

  • SKILL.md
  • reference/api_reference.md
  • reference/examples.md
  • reference/experiments.md
  • reference/protein_optimization.md

Open the folder on GitHubat commit 46b4d8b

Used in 9 other repositories

We found 13 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 9 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Adaptyv 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.

Adaptyv compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Adaptyv this skilldavila7/claude-code-templates32k9 repos~923Automated safety check: NotesMIT
Alphafold Database Fetch And Analyzegoogle-deepmind/science-skills3.2k2 repos~1.2kAutomated safety check: PassApache-2.0
Alphafoldadaptyvbio/protein-design-skills1643 repos~1.2kAutomated safety check: PassMIT
Pymol VisualizationChatMol/ChatMol373—~1.2kAutomated safety check: PassMIT
Complexa Binder DesignNVIDIA-BioNeMo/bionemo-agent-toolkit478—~3.1kAutomated safety check: NotesApache-2.0
Bindcraftadaptyvbio/protein-design-skills1643 repos~1.3kAutomated safety check: PassMIT

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Questions about Adaptyv

What does Adaptyv do?

Cloud laboratory platform for automated protein testing and validation. Adaptyv is an agent skill from davila7/claude-code-templates. Cloud laboratory platform for automated protein testing and validation.

When should I use Adaptyv?

Adaptyv fits situations like: designing proteins and needing experimental validation including binding assays; expression testing; thermostability measurements; enzyme activity assays.

How do I install Adaptyv in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill adaptyv -a claude-code`. Or copy the skill folder (cli-tool/components/skills/scientific/adaptyv in davila7/claude-code-templates) into .claude/skills/adaptyv in your project. Claude Code loads it when a task matches its description.

How do I install Adaptyv in Codex?

Run `npx skills add davila7/claude-code-templates --skill adaptyv -a codex`. Or copy the skill folder (cli-tool/components/skills/scientific/adaptyv in davila7/claude-code-templates) into .agents/skills/adaptyv in your project. Codex loads it when a task matches its description.

Can I use Adaptyv 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 davila7/claude-code-templates --skill adaptyv -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adaptyv, .gemini/skills/adaptyv, .github/skills/adaptyv and .opencode/skills/adaptyv in your project.

What does Adaptyv need to run?

Going by SKILL.md and its folder, Adaptyv needs the command-line tools its instructions call (uv) and credentials named ADAPTYV_API_KEY. Our summary lists: Python 3; A credential in ADAPTYV_API_KEY.

Does Adaptyv access the network?

SKILL.md names 1 domain. In commands or code: kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Adaptyv safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Adaptyv use?

Adaptyv is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Adaptyv use?

About 923 tokens (SKILL.md is roughly 3.7k 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 Adaptyv?

Skills that share tags, products or a category with Adaptyv: Alphafold Database Fetch And Analyze (google-deepmind/science-skills, 3.2k stars), Alphafold (adaptyvbio/protein-design-skills, 164 stars), Pymol Visualization (ChatMol/ChatMol, 373 stars) and Complexa Binder Design (NVIDIA-BioNeMo/bionemo-agent-toolkit, 478 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Adaptyv?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,483 GitHub stars. The repository holds 478 skills in this directory. The repository was last updated on October 9, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.