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 agentmods add skills/internscience/molclaw/molclaw-pack-sidechainsnpx skills add InternScience/MolClaw --skill molclaw-pack-sidechainsgit 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-pack-sidechains)<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-pack-sidechains"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-pack-sidechains.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 | $0.00031 | $0.00794 |
| Opus 5 | $0.00015 | $0.00397 |
| Sonnet 5 | $0.00006 | $0.00159 |
| Haiku 4.5 | $0.00003 | $0.00079 |
Grade A, and why
molclaw-pack-sidechains 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 4d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AttnPacker Sidechain Packing
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. Protein Sidechain Packing
The description of tool pack_sidechains.
Predict full-atom sidechain conformations from backbone PDBs for protein structure preparation workflows.
Args:
input_pdb (str): Input PDB file path, required.
device (str|None): Compute device such as cuda:0, default None (auto by source script).
chunk_size (int): Inference chunk size for long proteins, default 500.
no_post_process (bool): Skip rotamer post-processing for faster runtime, default False.
max_optim_iters (int): Maximum optimization iterations in post-process, default 250.
steric_wt (float): Steric clash penalty weight, default 1.0.
optim_repeats (int): Post-process optimization repeats, default 2.
dry_run (bool): Create a traceable run directory without running inference, default False.
Return:
status (str): 'success', 'error', or 'partial_success'.
msg (str): Human-readable execution message.
input_pdb (str): Input PDB path used for this run.
output_dir (str): Unique run directory under tool_result/pack_sidechains_result.
output_pdb (str): Expected or generated output PDB path.
device (str|None): Device value used for execution.
chunk_size (int): Chunk size used.
no_post_process (bool): Whether post-process was skipped.
max_optim_iters (int): Max optimization iterations used.
steric_wt (float): Steric weight used.
optim_repeats (int): Optimization repeats used.
dry_run (bool): Whether dry-run mode was used.
error_type (str, optional): Exception type when status is 'error'.
traceback (str, optional): Python traceback when status is 'error'.
How to use tool pack_sidechains :
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.
- 4d ago First seen · 92 lines · 31 tokens per session scan A e865724e3707
molclaw-pack-sidechains is a skill published in the GitHub repository InternScience/MolClaw (33 stars, last pushed 27d ago), licensed MIT. It adds 31 tokens to every session and 794 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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