Skills adaptyv

🧬

adaptyv

Name: adaptyv
Author: K-Dense-AI

Low Risk ⚡ Contains scripts🌐 Network access🔑 Env variables

Submit protein sequences for cloud lab validation

Also available from: davila7

Protein design requires experimental validation. Adaptyv provides API access to a cloud laboratory for automated testing of binding affinity, expression levels, thermostability, and enzyme activity. Get experimental results in approximately 21 days.

Supports: Claude Codex Code(CC)

📊 69 Adequate

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Using "adaptyv". Submit two antibody sequences for binding assays against PD-L1

Expected outcome:

Experiment submitted successfully
Experiment ID: exp_new123xyz
Status: submitted
Estimated completion: 2025-02-07
Target: Human PD-L1

Using "adaptyv". What is the status of my binding experiment?

Expected outcome:

Experiment: exp_abc123xyz
Status: processing
Progress: 65%
Current stage: assay
Updated: 2025-01-25T14:30:00Z

Using "adaptyv". Download and summarize the binding results

Expected outcome:

Results downloaded: exp_abc123xyz_results.json
Sequences tested: 12
Top binder: variant_7 (KD: 0.8 nM)
Confidence: high (R-squared: 0.98)

Security Audit

Low Risk

v4 • 1/17/2026

All 304 static findings are FALSE POSITIVES. The skill is legitimate scientific software for protein research. Scanner patterns triggered on: FASTA format headers (protein sequences in markdown code blocks), API calls to official platform endpoints, environment variable usage for API keys (recommended practice), and scientific notation (e.g., binding affinity values like 1.2e-9). No malicious behavior confirmed.

Files scanned

3,608

Lines analyzed

findings

Total audits

Risk Factors

⚡ Contains scripts (3)

SKILL.md:1-113 reference/api_reference.md:1-309 reference/examples.md:1-914

🌐 Network access (2)

SKILL.md:52-69 reference/examples.md:79-83

🔑 Env variables (2)

SKILL.md:22-25 reference/examples.md:13-16

Audited by: claude View Audit History →

Quality Score

Architecture

100

Maintainability

Content

Community

Security

Spec Compliance

What You Can Build

Antibody affinity testing

Submit antibody variants to measure binding affinity against target antigens and identify high-affinity candidates.

Sequence optimization validation

Use computational tools to design protein variants, then experimentally validate expression and stability predictions.

Catalytic activity screening

Screen enzyme variants for improved turnover, substrate affinity, and inhibitor sensitivity.

Try These Prompts

Submit binding assay

Submit my antibody sequences to Adaptyv for binding assays against human PD-L1. The sequences are in FASTA format and I want to measure KD values.

Check experiment status

Check the status of experiment exp_abc123xyz and tell me the current stage and estimated completion date.

Download results

Download the results from experiment exp_abc123xyz and parse the binding measurements into a table showing sequence, KD, kon, and koff values.

Run optimization pipeline

Optimize my protein sequences using NetSolP and SolubleMPNN, then submit the top 50 candidates to Adaptyv for expression testing with webhook notification.

Best Practices

Pre-screen sequences with computational tools (NetSolP, ESM) before experimental submission to reduce costs
Use webhooks instead of polling for experiment completion notifications
Include wild-type or reference sequences as controls in every batch submission

Avoid

Submitting sequences without validation - always run computational screening first
Polling for status instead of using webhooks - wastes API quota and adds delay
Ignoring FASTA format requirements - validate sequences locally before submission