synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.
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 synthetic-sciences/openscience --skill adaptyvgit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote 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/synthetic-sciences/openscience/adaptyv)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/adaptyv"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/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/synthetic-sciences/openscience/adaptyv"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/adaptyv.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 21 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 62 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00809 |
| Opus 5.5 | $0.00038 | $0.00324 |
| Sonnet 5.5 | $0.00019 | $0.00162 |
| Haiku 4.5 | $0.00010 | $0.00081 |
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 1mo 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( How it starts
The opening of the file, as written. The whole thing — 114 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.
- 1mo ago First seen · 114 lines · 95 tokens per session scan A 366ea0f3adc3
adaptyv is a skill published in the GitHub repository synthetic-sciences/openscience (4,266 stars, last pushed yesterday), licensed Apache-2.0. It adds 95 tokens to every session and 809 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
songsee
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
arxiv
Search arXiv papers by keyword, author, category, or ID.
research-paper-writing
Write ML papers for NeurIPS/ICML/ICLR: design→submit.
paper-revision-author
Revise independently drafted paper sections into one coherent LaTeX body before the abstract is written.
paper-plot-stub
Plot a results CSV (x, ybaseline, yours) as a two-line matplotlib chart and write a PDF. Demo-only.
knowledge-extension-ecosystem-lsp-code-intelligence
A codebase guide to LSP, the standard protocol behind editor features such as symbol queries, file diagnostics, and language-aware code information.