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 xjtulyc/awesome-rosetta-skills --skill ase-atomisticgit clone --depth 1 https://github.com/xjtulyc/awesome-rosetta-skillsWrote 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/xjtulyc/awesome-rosetta-skills/ase-atomistic)<a href="https://agentmods.dev/skills/xjtulyc/awesome-rosetta-skills/ase-atomistic"><img src="https://agentmods.dev/badge/skills/xjtulyc/awesome-rosetta-skills/ase-atomistic/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/xjtulyc/awesome-rosetta-skills/ase-atomistic"><img src="https://agentmods.dev/badge/skills/xjtulyc/awesome-rosetta-skills/ase-atomistic.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 | $0.00032 | $0.09363 |
| Opus 5 | $0.00016 | $0.04681 |
| Sonnet 5 | $0.00006 | $0.01873 |
| Haiku 4.5 | $0.00003 | $0.00936 |
Grade A, and why
ase-atomistic 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 12d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 12d ago First seen · 1,041 lines · 32 tokens per session scan A 8daf67c5c600
ase-atomistic is a skill published in the GitHub repository xjtulyc/awesome-rosetta-skills (34 stars, last pushed 5mo ago), with no licence file. It adds 32 tokens to every session and 9,363 once invoked, about $0.0002 per session on Opus 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
ase-framework
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pymatgen-structure
Structure manipulation and crystal analysis workflows based on pymatgen. USE WHEN you need to read/write common atomistic formats (CIF, POSCAR, XYZ), build supercells, perform site substitution/doping, inspect symmetry (space group), or compute local structure descriptors for materials tasks.
xtbloom-run-python-inference
Write, review, and run high-level xTBloom Python GFN2-xTB inference with Calculator, Structure, and BatchCalculator, including single systems, repeated geometry updates, heterogeneous ragged batches, backend selection, units, finite-temperature meaning, and peer-local failure handling. Use for ordinary NumPy-based…
dpdata-driver
Use dpdata Python Driver plugins to label systems (energies/forces/virials) via System.predict(), list available drivers, and build Driver objects (ase/deepmd/gaussian/sqm/hybrid). Use when working with dpdata Python API (not CLI) and you need driver-based energy/force prediction, plugin registration keys, or examples…
rdkit
Use when working with RDKit for cheminformatics in Python. Covers molecular I/O, property calculation, Lipinski filters, fingerprints, similarity, 3D conformer generation, reactions, fragmentation, substructure search, MCS, stereochemistry, and tautomers.
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.