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/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/internscience/molclaw/molclaw-openawsem-tool"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-openawsem-tool.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 | $0.00065 | $0.01617 |
| Opus 5.5 | $0.00026 | $0.00647 |
| Sonnet 5.5 | $0.00013 | $0.00323 |
| Haiku 4.5 | $0.00006 | $0.00162 |
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 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenAWSEM Simulation and Trajectory Extraction
Invocation
Use the exact tool name and parameter schema exposed by the current harness. Tool names in SDK examples below are raw MCP names, not model-facing aliases. Local files must be uploaded with molclaw-file-transfer before a server tool can use them. Repair PDB inputs first when the workflow requires it.
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.
- 1mo ago Changed · -1 lines · +42 tokens per session fdd944c58ccc
- 1mo 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 (38 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,617 once invoked, about $0.0003 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 2026-08-30.
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