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 learningmatter-mit/AtomisticSkills --skill drug-protein-ligand-mdgit clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkillsWrote 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/learningmatter-mit/atomisticskills/drug-protein-ligand-md)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/drug-protein-ligand-md"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/drug-protein-ligand-md/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/learningmatter-mit/atomisticskills/drug-protein-ligand-md"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/drug-protein-ligand-md.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 | $0.00042 | $0.01571 |
| Opus 5 | $0.00021 | $0.00785 |
| Sonnet 5 | $0.00008 | $0.00314 |
| Haiku 4.5 | $0.00004 | $0.00157 |
Grade A, and why
drug-protein-ligand-md 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 10d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
drug-protein-ligand-md
Goal
To run a complete protein-ligand molecular dynamics simulation using OpenMM, starting from a system bundle produced by drug-complex-system-builder. The workflow includes:
- Energy minimization
- NVT equilibration with positional restraints on heavy atoms
- NPT equilibration with restraints gradually released
- NPT production run
The output is a DCD trajectory + final state checkpoint suitable for drug-trajectory-analysis.
Instructions
1. Prepare inputs
Required from drug-complex-system-builder:
system.xml: serialized OpenMM Systemcomplex_solvated.pdb: solvated complex PDB (used as topology reference)
2. Run the simulation
# Env: drugmd-agent
python .agents/skills/drug-protein-ligand-md/scripts/run_md.py \
--system_xml md/system/system.xml \
--input_pdb md/system/complex_solvated.pdb \
--temperature 300 \
--pressure 1.0 \
--timestep 4.0 \
--minimize_steps 5000 \
--equil_nvt_steps 25000 \
--equil_npt_steps 50000 \
--production_steps 2500000 \
--restraint_k 50.0 \
--reporting_interval 5000 \
--checkpoint_interval 25000 \
--output_dir md/run/
Key parameters:
--temperature: simulation temperature in Kelvin (default: 300).--pressure: target pressure in atm (default: 1.0).--timestep: integration timestep in fs (default: 4.0). 4 fs is safe with hydrogen mass repartitioning (HMR) from the system builder; use 2 fs without HMR.--minimize_steps: max minimization steps (default: 5000). Set to 0 to skip.--equil_nvt_steps: NVT equilibration steps with restraints on protein/ligand heavy atoms (default: 25000 = 100 ps at 4 fs).--equil_npt_steps: NPT equilibration steps with restraints released (default: 50000 = 200 ps).--production_steps: production NPT steps (default: 2500000 = 10 ns at 4 fs).--restraint_k: restraint force constant for equilibration in kJ/mol/nm^2 (default: 50.0).--reporting_interval: write trajectory frame every N steps (default: 5000 = 20 ps).--checkpoint_interval: write checkpoint every N steps (default: 25000).
What ships with it
3 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.
- 10d ago First seen · 138 lines · 42 tokens per session scan A 005ed4358252
drug-protein-ligand-md is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (163 stars, last pushed 7d ago), licensed MIT. It adds 42 tokens to every session and 1,571 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.
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