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adaptyv

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 f

Quelle prüfenAuf GitHub ansehen
Preis unbestätigt★ 3,130 GitHub-StarsVerzeichnis aktualisiert · 2. Sept. 2026agent-skill

Übersicht

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.

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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:
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 support@adaptyvbio.com for access requests or questions
  • Suitable for high-throughput AI-driven protein design workflows
Dateimetadaten
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.
Originaltext anzeigen
---
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

Quelle prüfen

Preis und Betriebskosten

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Apache-2.0
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Skill-Quelle erfasst

Ein Anleitungspfad ist erfasst. Das ist kein Ausführungstest und keine Sicherheits- oder Kompatibilitätsgarantie.

Vor Installation prüfen: Automatische Installation vermeiden

Lizenz: Apache-2.0

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill depends on an external API that is in alpha/beta, so endpoints and behavior may change without notice.
  • The documentation does not explicitly mention rate limits or error handling strategies for the API.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Vollständiges Audit öffnen

Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.

Mit einer kleinen Aufgabe beginnen

  1. 1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
  2. 2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
  3. 3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.

Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.

Quelle und Nutzungshinweise

Erfasst

Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.

Quell-Repository
foryourhealth111-pixel/Vibe-Skills
Lizenz
Apache-2.0
Version
1.0.0
Letzter GitHub-Push
31. Aug. 2026
Verzeichnis aktualisiert
2. Sept. 2026

Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.

Qualität

79/100

Stark

Vertrauen

60/100

Nur Sandbox

Audit

77/100

Prüfung nötig

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill depends on an external API that is in alpha/beta, so endpoints and behavior may change without notice.
  • The documentation does not explicitly mention rate limits or error handling strategies for the API.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Verified installs
—
Ergebnisse
—

Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.

Agent-Zugang

Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.

Weitere Details
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    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20adaptyv%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/foryourhealth111-pixel-adaptyv/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/foryourhealth111-pixel-adaptyv"
  }
}

Für Ersteller

Quelle des Eintrags

Registry-indexiert

Beanspruchbar

Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.

Indexiert von
OpenAgentSkill Community-Index

Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.

Diesen Skill beanspruchen

Eigentümeranspruch

Diesen Skill-Eintrag beanspruchen

Dieser Registry-indexiert-Eintrag wird foryourhealth111-pixel zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.

Share-Kit

Creator-Backlink-Kit

Evidenz-Badges in deine README einfügen

Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/foryourhealth111-pixel-adaptyv?metric=listed&label=Listed)](https://www.openagentskill.com/skills/foryourhealth111-pixel-adaptyv?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/foryourhealth111-pixel-adaptyv?metric=trust&label=Trust)](https://www.openagentskill.com/skills/foryourhealth111-pixel-adaptyv?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/foryourhealth111-pixel-adaptyv?metric=audit&label=Audit)](https://www.openagentskill.com/skills/foryourhealth111-pixel-adaptyv/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/foryourhealth111-pixel-adaptyv?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/foryourhealth111-pixel-adaptyv?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Community-Signal

Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.