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-goca-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-goca-tool)<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-goca-tool"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-goca-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 | $0.00027 | $0.00735 |
| Opus 5 | $0.00014 | $0.00367 |
| Sonnet 5 | $0.00005 | $0.00147 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
molclaw-goca-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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GoCa Pipeline
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. -
GoCa executable path is fixed by the managed wrapper to
/data/lwj/wll/code/drug/GoCa/GoCa.
Usage
1. GoCa Pipeline
The description of tool goca_pipeline.
Runs GoCa coarse-grained setup and optional full MD workflow for protein structure relaxation and trajectory generation.
Args:
protein_pdb (str): Input protein PDB path, required.
full_md (bool): Whether to run EM, production MD, and post-processing, default True.
temperature (float): GoCa reduced temperature used for MD, default 45.0.
md_time (float): MD simulation length in ps, default 12000.0.
gpu_ids (str | None): Optional GROMACS GPU device IDs, default None.
dry_run (bool): Create tracked run directory and return normalized parameters without execution, default False.
Return:
status (str): success, partial_success, or error.
msg (str): Human-readable run summary.
output_dir (str): Run-specific directory under tool_result/goca_pipeline_result.
work_dir (str): Relative GoCa working directory under output_dir.
protein_pdb (str): Resolved input protein PDB absolute path.
full_md (bool): Effective full_md value used by wrapper.
temperature (float): Effective reduced temperature used by wrapper.
md_time (float): Effective MD time in ps used by wrapper.
gpu_ids (str | None): Effective GPU IDs used by wrapper.
dry_run (bool): Effective dry_run value used by wrapper.
key_files (dict): Key output files relative to output_dir.
analysis_dir (str | None): Analysis directory relative to output_dir when generated.
How to use tool goca_pipeline :
response = await client.session.call_tool(
"goca_pipeline",
arguments={
"protein_pdb": "/path/to/input.pdb",
"full_md": True,
"md_time": 1000.0,
"temperature": 45.0,
"gpu_ids": None,
"dry_run": False
}
)
result = client.parse_result(response)
key_output = result["output_dir"]
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 · 90 lines · 27 tokens per session scan A b5bab806b82f
molclaw-goca-tool is a skill published in the GitHub repository InternScience/MolClaw (33 stars, last pushed 1mo ago), licensed MIT. It adds 27 tokens to every session and 735 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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