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 agentmods add skills/synthetic-sciences/openscience/pocket-detectionnpx skills add synthetic-sciences/openscience --skill pocket-detectiongit 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/pocket-detection)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/pocket-detection"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/pocket-detection.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.03219 |
| Opus 5 | $0.00020 | $0.01610 |
| Sonnet 5 | $0.00008 | $0.00644 |
| Haiku 4.5 | $0.00004 | $0.00322 |
Grade B, and why
pocket-detection scanned grade B 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 yesterday.
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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
# Ubuntu/Debian: sudo apt-get install fpocket How it starts
The opening of the file, as written. The whole thing — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pocket Detection & Druggability Assessment
Overview
This skill provides multi-method binding pocket detection on protein structures, druggability scoring, pocket visualization, and cross-structure pocket comparison. It is the first dedicated step in any structure-based drug design workflow — identifying where on a protein a small molecule can bind before docking or de novo design begins.
Key capabilities:
- Three detection methods: grid-based cavity scan, fpocket (alpha spheres), P2Rank (machine learning)
- Druggability scoring: 6-axis weighted assessment (volume, hydrophobicity, enclosure, depth, H-bond capacity, aromaticity)
- Visualization: summary panels, residue composition, druggability radar, method comparison plots
- Cross-structure comparison: match pockets across apo/holo, wild-type/mutant, or predicted/experimental structures
When to Use This Skill
Use the pocket-detection skill when you need to:
- Find binding sites on a protein structure before docking
- Assess druggability of detected pockets (can a drug-like molecule bind here?)
- Compare pockets across multiple structures (e.g., apo vs holo, WT vs mutant)
- Visualize pocket properties for reports or publications
- Validate binding sites using multiple detection methods for consensus
- Identify allosteric sites beyond the obvious orthosteric pocket
Trigger phrases: "find binding pocket", "detect active site", "druggability assessment", "pocket detection", "where does the ligand bind", "compare binding sites"
Do NOT use this skill for:
- Actually docking ligands into pockets (use
molecular-docking) - Predicting how tightly a ligand binds (use
binding-affinity) - Protein structure prediction (use
structure-predictionfirst, then this) - Protein-protein interaction surfaces (use ClusPro or HDOCK)
Related Skills
- molecular-docking: Dock ligands into detected pockets. This skill's JSON output feeds directly into
dock.py --center_x/y/z. - binding-affinity: Score docked poses for binding strength. Run after docking.
- structure-prediction: Predict protein structure from sequence when no experimental PDB is available. Run before this skill.
What ships with it
6 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.
- yesterday First seen · 327 lines · 41 tokens per session scan B 2c1437963253
pocket-detection is a skill published in the GitHub repository synthetic-sciences/openscience (3,473 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 3,219 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
meta-paper-write
Use this meta-skill instead of answering directly when the current user asks to draft or produce a new academic/research paper or LaTeX manuscript. It uses multi-skill orchestration for manuscript workflows that need source search, citation planning, experiment or figure/table placeholders, drafting, length checks…
paper-revision-author
Revise independently drafted paper sections into one coherent LaTeX body before the abstract is written.
paper-section-author
Write one publication-style research-paper section as a bounded, citation-grounded LaTeX fragment from a writing plan, outline, citation plan, and optional figure/table context.
meta-arxiv-daily-digest-deck
Fetch the day's top arXiv submissions in a chosen category, write a structured per-paper digest, render the digest as a PPTX deck (one slide per paper), and persist the digest to long-term memory. Use for a daily 'arxiv morning briefing' — manual fire or cron-scheduled.
paper-quality-gate
Deterministic pre-compile gate for meta-paper-write. Enforces length/citation verdicts and rejects unsupported empirical-result claims when no user evidence was supplied.
paper-latex-sanitizer
Deterministically normalize safe LaTeX punctuation and replace unsupported forecast magnitudes with explicit placeholders before meta-paper-write publication gates run.