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 InternScience/MolClaw --skill molclaw-openawsem-toolgit clone --depth 1 https://github.com/InternScience/MolClawWrote 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/internscience/molclaw/molclaw-openawsem-tool)<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-openawsem-tool"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-openawsem-tool.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 | $0.00023 | $0.01585 |
| Opus 5 | $0.00012 | $0.00792 |
| Sonnet 5 | $0.00005 | $0.00317 |
| Haiku 4.5 | $0.00002 | $0.00159 |
Grade A, and why
molclaw-openawsem-tool 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.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenAWSEM Simulation and Trajectory Extraction
Note:
- Local files are not directly accessible by the server. Please upload them to the server using
molclaw-file-transferbefore execution. - For PDB file inputs, it is recommended to preprocess them using
molclaw-pdbfixerbefore execution. - Please refer to skill
molclaw-scp-serverto complete tool invocation.
Usage
1. OpenAWSEM Simulation
The description of tool openawsem_sim.
Run OpenAWSEM coarse-grained protein simulation for annealing or NVT workflows in structure screening and folding studies.
Args:
sim_dir (str|None): Simulation directory containing *-openmmawsem.pdb or *_openmmawsem.pdb, default None.
pdb (str|None): PDB file path or PDB ID used by awsem_create when sim_dir is not provided, default None.
steps (float): Simulation step count, default 1e5.
mode (str): Temperature control mode in {annealing, nvt}, default annealing.
temperature (float): NVT temperature in Kelvin passed to source script argument --temperature, default 300.0.
platform (str): OpenMM platform in {CPU, CUDA, OpenCL}, default CPU.
use_frag_mem (bool): Whether to use fragment memory instead of single memory, default False.
compute_q (bool): Whether to enable Q-value related terms when available, default False.
dry_run (bool): Whether to validate setup without running MD steps, default False.
gpu_id (str): GPU device index for CUDA/OpenCL platform, default 0.
Return:
status (str): success, error, or partial_success execution status.
msg (str): Human-readable execution summary.
output_dir (str): Unique run directory under tool_result/openawsem_result.
simulation_dir (str): Effective simulation directory used by the delegated source script.
steps (float): Effective step count used in this run.
mode (str): Effective simulation mode used in this run.
temperature (float): Effective NVT temperature used in this run.
platform (str): Effective compute platform used in this run.
dry_run (bool): Effective dry-run flag used in this run.
output_files (dict): Key output file paths such as final PDB, energy log, checkpoint, and trajectory files.
metrics (dict): Parsed summary metrics such as energy log line count and last log line when available.
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 · 193 lines · 23 tokens per session scan A bfa697691460
molclaw-openawsem-tool is a skill published in the GitHub repository InternScience/MolClaw (33 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 1,585 once invoked, about $0.0001 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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