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adaptyvadaptyv 搜索

Agent Skill

adaptyv 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

606

周安装

25

GitHub Stars

公开资料未说明

下载量

198
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:adaptyv(adaptyv 搜索)
来源仓库:https://github.com/microck/ordinary-claude-skills
仓库路径:skills/adaptyv
安装命令:
npx skills add microck/ordinary-claude-skills --skill "adaptyv"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add microck/ordinary-claude-skills --skill "adaptyv"

简介

快速检索并筛选相关信息,辅助技能发现与安装。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中需要关键词定位的场景。
  • 使用 npx 命令从指定仓库添加 adaptyv 技能模块。
  • 需确保网络连通性及对目标仓库的访问权限。adaptyv 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 建议核对原始 README 以了解实际功能边界。

SKILL.md

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 [email protected] to request API access (platform is in alpha/beta)
  2. Receive your API access token
  3. Set environment variable:
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:

uv pip install requests python-dotenv

Basic Usage

Submit protein sequences for testing:

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 [email protected] for access requests or questions
  • Suitable for high-throughput AI-driven protein design workflows

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

31.29%
按下载量换算62

Codex

21.99%
按下载量换算44

Antigravity

18.34%
按下载量换算36

windsurf

11.35%
按下载量换算22

Gemini CLI

7.45%
按下载量换算15

OpenCode

3.54%
按下载量换算7

安全审计

暂无安全审计结果可展示。

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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