Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ma-compbio-lab/SkillFoundrynpx agentmods add skills/ma-compbio-lab/skillfoundry/openmm-forcefield-assignment-starterWrote 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/ma-compbio-lab/skillfoundry/openmm-forcefield-assignment-starter)<a href="https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/openmm-forcefield-assignment-starter"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/openmm-forcefield-assignment-starter.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 5.1 | $0.00000 | $0.00267 |
| Opus 5 | $0.00000 | $0.00133 |
| Sonnet 5 | $0.00000 | $0.00053 |
| Haiku 4.5 | $0.00000 | $0.00027 |
Grade A, and why
openmm-forcefield-assignment-starter 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 7d 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.
What it actually says
OpenMM Force-Field Assignment Starter
Use this skill to assign a simple water force field to a tiny PDB topology with OpenMM and summarize the resulting system.
What it does
- Loads a small example PDB topology.
- Applies OpenMM
tip3p.xmlwith deterministiccreateSystemsettings. - Reports particle, residue, constraint, and force-class counts in JSON.
When to use it
- You need a verified local starter for
force-field assignment. - You want a small, deterministic system-construction check before longer OpenMM workflows.
Example
./slurm/envs/chem-tools/bin/python skills/computational-chemistry-and-molecular-simulation/openmm-forcefield-assignment-starter/scripts/run_openmm_forcefield_assignment.py \
--input skills/computational-chemistry-and-molecular-simulation/openmm-forcefield-assignment-starter/examples/two_waters.pdb \
--out scratch/openmm-forcefield/summary.json
Verification
- Skill-local tests:
python3 -m unittest discover -s skills/computational-chemistry-and-molecular-simulation/openmm-forcefield-assignment-starter/tests -p 'test_*.py' - Repository smoke target:
make smoke-openmm-forcefield
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.
- 7d ago First seen · 28 lines · 0 tokens per session scan A f9b1a0520f9d
openmm-forcefield-assignment-starter is a skill published in the GitHub repository ma-compbio-lab/SkillFoundry (38 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 267 tokens. 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.
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