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-prolif-toolnpx skills add InternScience/MolClaw --skill molclaw-prolif-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-prolif-tool)<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-prolif-tool"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-prolif-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 | $0.00030 | $0.02924 |
| Opus 5 | $0.00015 | $0.01462 |
| Sonnet 5 | $0.00006 | $0.00585 |
| Haiku 4.5 | $0.00003 | $0.00292 |
Grade A, and why
molclaw-prolif-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 6d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ProLIF Multi-Scenario Analysis Toolkit
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.
[!IMPORTANT] Tool Priority: For single-structure interaction analysis (one complex, one pose), use
molclaw-interaction-visualizer(local script) as the primary tool instead ofprolif_pdb. ProLIF remains the primary tool for:
prolif_docking— batch docking pose fingerprint comparisonprolif_md— MD trajectory interaction dynamicsprolif_protein_protein— protein-protein trajectory interface profilingThese capabilities are NOT available in interaction-visualizer.
[!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 usingmolclaw-pdbfixerbefore execution.
Usage
1. MD Trajectory Fingerprinting
The description of tool prolif_md.
Compute ProLIF fingerprints for an MD trajectory and return standardized summary metrics.
Args:
topology_path (str): Path to the topology file (e.g., .psf, .pdb, .prmtop).
trajectory_path (str): Path to the trajectory file to analyze.
ligand_selection (str): Selection string identifying ligand atoms.
protein_selection (str): Selection string for protein atoms. Default: 'protein'.
interactions (List[str]|None): Optional interaction types to compute (e.g., Hydrophobic, HBDonor).
count (bool): If True, compute interaction counts instead of fingerprints. Default: False.
vicinity_cutoff (float|None): Optional distance cutoff for vicinity interactions.
params_json (str|None): Optional JSON parameter file path for ProLIF interaction settings.
start (int|None): Optional start frame index.
stop (int|None): Optional stop frame index (exclusive).
step (int|None): Optional frame stride.
residues (List[str]|None): Optional explicit residue list to include.
all_residues (bool): If True, include all residues in analysis. Default: False.
Return:
status (str): 'success' or 'error'.
msg (str): Human-readable summary or error message.
command (str): The executed command label ('md').
output_dir (str|None): Run-specific directory under tool_result/prolif_result.
output_file (str|None): Path to the generated CSV file.
n_frames (int|None): Number of processed frames.
n_interactions (int|None): Number of interaction columns in output.
frequent_interactions (List[dict]|None): High-frequency interactions (>30%) with keys 'interaction' and 'frequency'.
result_summary (dict|None): Full summary dictionary from the wrapper.
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.
- 6d ago First seen · 318 lines · 30 tokens per session scan A 99134e3eb321
molclaw-prolif-tool is a skill published in the GitHub repository InternScience/MolClaw (33 stars, last pushed 29d ago), licensed MIT. It adds 30 tokens to every session and 2,924 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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