adaptyv

davila7/claude-code-templates · updated Apr 8, 2026

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$npx skills add https://github.com/davila7/claude-code-templates --skill adaptyv
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summary

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.

skill.md

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
how to use adaptyv

How to use adaptyv on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add adaptyv
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill adaptyv

The skills CLI fetches adaptyv from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/adaptyv

Reload or restart Cursor to activate adaptyv. Access the skill through slash commands (e.g., /adaptyv) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.539 reviews
  • Aditi Liu· Dec 12, 2024

    Useful defaults in adaptyv — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yusuf Reddy· Dec 8, 2024

    We added adaptyv from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ama Nasser· Dec 4, 2024

    adaptyv fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Emma Srinivasan· Nov 27, 2024

    Keeps context tight: adaptyv is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Evelyn Farah· Nov 19, 2024

    Registry listing for adaptyv matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aditi Farah· Nov 3, 2024

    I recommend adaptyv for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aditi Abebe· Oct 22, 2024

    adaptyv reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Emma Rao· Oct 18, 2024

    adaptyv has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Emma Mensah· Oct 10, 2024

    adaptyv fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • James Lopez· Sep 25, 2024

    Useful defaults in adaptyv — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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