Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add silverstein/claude-scientific-skills-desktop --skill adaptyvgit clone --depth 1 https://github.com/silverstein/claude-scientific-skills-desktopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/adaptyv)<a href="https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/adaptyv"><img src="https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/adaptyv/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/adaptyv"><img src="https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/adaptyv.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.00791 |
| Opus 5 | $0.00048 | $0.00396 |
| Sonnet 5 | $0.00019 | $0.00158 |
| Haiku 4.5 | $0.00010 | $0.00079 |
Grade A, and why
adaptyv scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.post( This is a copy
89% identical to adaptyv — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Contact [email protected] to request API access (platform is in alpha/beta)
- Receive your API access token
- 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
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 115 lines · 95 tokens per session scan A b6013c70b2cf
adaptyv is a skill published in the GitHub repository silverstein/claude-scientific-skills-desktop (22 stars, last pushed 5mo ago), licensed MIT. It adds 95 tokens to every session and 791 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 89% identical to adaptyv, differing in 11 lines, and is treated as a copy.
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admet_genetic
ADMET-guided genetic molecule optimization workflow from seed SMILES; use when the agent needs to build or run an RDKit/SA-Score/ADMET-AI GA pipeline for molecule optimization, enforce molecule lineage logs, render optimization-history HTML dashboards, and write candidate triage reports.
bioprobench
Score an LLM's biological-protocol reasoning on the BioProBench benchmark: protocol QA, step ordering, error detection, protocol generation, and LLM-judged error reasoning; or generate the responses.
alphafold2
Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency…
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bio-causal-genomics-heritability-partitioning
Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML…