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 zinc-databasegit 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/zinc-database)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/zinc-database"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/zinc-database.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00047 | $0.03524 |
| Opus 5 | $0.00023 | $0.01762 |
| Sonnet 5 | $0.00009 | $0.00705 |
| Haiku 4.5 | $0.00005 | $0.00352 |
Grade A, and why
zinc-database scanned grade A with 2 findings 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 4d 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.
curl "https://cartblanche22.docking.org/[email protected]_fields=smiles,zinc_id" Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run(['curl', url], capture_output=True, text=True) Copies of this mod
2 near-identical copies found in the catalogue:
- zinc-database — 97% identical, 7 lines differ
- zinc-database — 95% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 404 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ZINC Database
Overview
ZINC is a freely accessible repository of 230M+ purchasable compounds maintained by UCSF. Search by ZINC ID or SMILES, perform similarity searches, download 3D-ready structures for docking, discover analogs for virtual screening and drug discovery.
When to Use This Skill
This skill should be used when:
- Virtual screening: Finding compounds for molecular docking studies
- Lead discovery: Identifying commercially-available compounds for drug development
- Structure searches: Performing similarity or analog searches by SMILES
- Compound retrieval: Looking up molecules by ZINC IDs or supplier codes
- Chemical space exploration: Exploring purchasable chemical diversity
- Docking studies: Accessing 3D-ready molecular structures
- Analog searches: Finding similar compounds based on structural similarity
- Supplier queries: Identifying compounds from specific chemical vendors
- Random sampling: Obtaining random compound sets for screening
Database Versions
ZINC has evolved through multiple versions:
- ZINC22 (Current): Largest version with 230+ million purchasable compounds and multi-billion scale make-on-demand compounds
- ZINC20: Still maintained, focused on lead-like and drug-like compounds
- ZINC15: Predecessor version, legacy but still documented
This skill primarily focuses on ZINC22, the most current and comprehensive version.
Access Methods
Web Interface
Primary access point: https://zinc.docking.org/ Interactive searching: https://cartblanche22.docking.org/
API Access
All ZINC22 searches can be performed programmatically via the CartBlanche22 API:
Base URL: https://cartblanche22.docking.org/
All API endpoints return data in text or JSON format with customizable fields.
Core Capabilities
1. Search by ZINC ID
Retrieve specific compounds using their ZINC identifiers.
Web interface: https://cartblanche22.docking.org/search/zincid
API endpoint:
curl "https://cartblanche22.docking.org/[email protected]_fields=smiles,zinc_id"
What ships with it
1 file 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.
- 4d ago First seen · 404 lines · 47 tokens per session scan A 3834d2f8c9fd
zinc-database is a skill published in the GitHub repository synthetic-sciences/openscience (3,501 stars, last pushed today), licensed Apache-2.0. It adds 47 tokens to every session and 3,524 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). 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.
google-workspace-setup
One-time setup for gws: install, OAuth, scopes, auto-approve.