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 structure-analysisgit 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/structure-analysis)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/structure-analysis"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/structure-analysis/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/structure-analysis"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/structure-analysis.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 | $0.00141 | $0.02082 |
| Opus 5.5 | $0.00056 | $0.00833 |
| Sonnet 5.5 | $0.00028 | $0.00416 |
| Haiku 4.5 | $0.00014 | $0.00208 |
Grade A, and why
structure-analysis 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Protein structure analysis
One PDB entry yields different residue counts, interface lists and hydrogen-bond totals depending on how waters, HETATM records, alternate locations and symmetry copies were treated. Those choices, and every distance or angle cutoff, are part of the result and are reported with it.
Files and identity
- Prefer PDBx/mmCIF over the legacy PDB format: PDB files break above 99,999 atoms and
62 chains, truncate chain IDs to one character and have no entity concept. Download
https://files.rcsb.org/download/<id>.cifor use BiopythonPDBList().retrieve_pdb_file("1abc", pdir=".", file_format="mmCif"). Record the entry id, the model used (NMR ensembles have many; state the index) and the download date. - Chains and entities: mmCIF has
label_asym_id(internal chain),auth_asym_id(the author chain that papers and viewers use) andlabel_entity_id; a homodimer is one entity with two chains. Residue numbering isauth_seq_id(author numbering with gaps, insertion codes and negatives) orlabel_seq_id(1..n over the entity sequence). UniProt numbering is a third scheme, mapped by SIFTS. Say which one every residue number in the report follows. - HETATM policy: ligands, ions, modified residues inside the polymer (MSE, SEP, TPO) and
waters (HOH, DOD) are all HETATM. Decide and state whether waters are removed, ions
kept, and modified residues counted as protein. Biopython encodes this in
residue.id[0](" "standard,"W"water,"H_XXX"hetero) andBio.PDB.Polypeptide.is_aa(res, standard=True); gemmi offersst.remove_waters(),st.remove_ligands_and_waters(),st.remove_hydrogens()andResidue.het_flag. Callst.setup_entities()after reading PDB files with gemmi. - Alternate locations: pick one conformer consistently. Biopython's
PDBParserwraps them inDisorderedAtomobjects that default to the highest occupancy (atom.is_disordered()); gemmist.remove_alternative_conformations()keeps the first; MDAnalysis selects withaltloc A. Counting all altlocs doubles some contacts. - Insertion codes: a Biopython residue id is
(hetflag, resseq, icode), so 52 and 52A are distinct residues; parsing the number alone merges them. Antibody numbering schemes rely on them. - Assemblies: the asymmetric unit may hold half a dimer or two copies of a monomer. The
biological assembly applies the operators in
_pdbx_struct_assembly(REMARK 350). gemmi:gemmi.make_assembly(st.assemblies[0], st[0], gemmi.HowToNameCopiedChain.AddNumber)orst.transform_to_assembly("1", how); PyMOLset assembly, 1beforefetch; ChimeraXsym #1 assembly 1; RCSB serves<id>-assembly1.cif. Interfaces across symmetry mates exist only in the assembly. Report which assembly, or that the asymmetric unit was used. - Hydrogens: crystal structures rarely include them. Angle-based hydrogen-bond criteria
need added hydrogens (PDBFixer or OpenMM
Modeller.addHydrogens, PyMOLh_add, ChimeraXaddh); heavy-atom-only criteria are the alternative. State which.
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 · 110 lines · 141 tokens per session scan A 56a493ca9dd2
structure-analysis is a skill published in the GitHub repository synthetic-sciences/openscience (4,025 stars, last pushed today), licensed Apache-2.0. It adds 141 tokens to every session and 2,082 once invoked, about $0.0006 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 2026-09-15.
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.