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 drug-designgit 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/drug-design)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/drug-design"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/drug-design/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/drug-design"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/drug-design.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00044 | $0.02779 |
| Opus 5.5 | $0.00018 | $0.01112 |
| Sonnet 5.5 | $0.00009 | $0.00556 |
| Haiku 4.5 | $0.00004 | $0.00278 |
Grade A, and why
drug-design scanned grade A with 0 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 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drug Design Pipeline
Overview
This skill provides a deterministic pipeline orchestrator (pipeline.py) that auto-chains multiple drug discovery skills into reproducible workflows. Instead of manually invoking 10+ scripts in the correct order, the agent runs a single command that handles file wiring, schema validation, and manifest logging at every stage.
Why a script instead of manual chaining:
- Guarantees correct execution order — the agent cannot skip or reorder stages
- Validates I/O contracts between stages — catches schema mismatches early
- Logs every invocation to
_script_manifest.jsonl— critique agent can verify the full trace - Stops on first failure with clear diagnostics — no silent errors
Pipeline Mode Selection
Choose the mode based on what the user wants:
| User Intent | Mode | Command |
|---|---|---|
| "Find drugs for target X" | full |
--mode full --protein target.pdb |
| "Optimize this hit compound" | lead-opt |
--mode lead-opt --protein target.pdb --ligand hit.sdf |
| "Screen this library" | screen |
--mode screen --protein target.pdb --library compounds.sdf |
| "Is this target druggable?" | assess |
--mode assess --protein target.pdb |
| "Design molecules for this pocket" | denovo |
--mode denovo --protein target.pdb |
Trigger phrases: "drug discovery pipeline", "find drugs", "design drugs", "screen compounds", "druggability assessment", "de novo design", "lead optimization"
Quick Start
Full Pipeline (target → drug candidates)
python scripts/pipeline.py \
--mode full \
--protein target.pdb \
--output-dir results/ \
--top-n 10
Lead Optimization (improve an existing hit)
python scripts/pipeline.py \
--mode lead-opt \
--protein target.pdb \
--ligand hit_compound.sdf \
--output-dir lead_opt_results/ \
--top-n 20
Virtual Screening (screen a compound library)
python scripts/pipeline.py \
--mode screen \
--protein target.pdb \
--library compound_library.sdf \
--output-dir screening_results/ \
--top-n 50
What ships with it
2 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 · 275 lines · 44 tokens per session scan A ae45e28768fc
drug-design is a skill published in the GitHub repository synthetic-sciences/openscience (4,121 stars, last pushed 2d ago), licensed Apache-2.0. It adds 44 tokens to every session and 2,779 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
end-to-end-protein-design-workflow
End-to-end protein design pipeline guide across preparation, generation, validation, and filtering. Use this skill when: (1) Starting a new protein design project, (2) Need step-by-step workflow guidance, (3) Understanding the full design pipeline, (4) Planning compute resources and timelines, (5) Integrating multiple…
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.