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-hdock-toolnpx skills add InternScience/MolClaw --skill molclaw-hdock-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-hdock-tool)<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-hdock-tool"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-hdock-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 | $0.00024 | $0.01090 |
| Opus 5 | $0.00012 | $0.00545 |
| Sonnet 5 | $0.00005 | $0.00218 |
| Haiku 4.5 | $0.00002 | $0.00109 |
Grade A, and why
molclaw-hdock-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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HDOCK Protein Docking
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. HDOCK Protein Docking
The description of tool hdock_tool.
Run HDOCKlite protein-protein/protein-peptide docking and return the unique run directory, key files, and summary metrics for structure-based screening workflows. Inputs must be non-degenerate PDB coordinate files; SDF/PDBQT inputs are rejected before HDOCK is launched. The server chooses the output directory and may remap the partner chain in its internal copy to avoid receptor/partner chain collisions.
Args:
receptor (str): Receptor PDB file path.
ligand (str): Ligand or partner PDB file path.
nmax (int): Number of docking models to generate (default 100).
no_complex (bool): Disable complex structure generation (default False).
angle (int): Rotation sampling interval in degrees (default 15).
rsite (str|None): Optional receptor binding-site residue file.
lsite (str|None): Optional ligand binding-site residue file.
Return:
status (str): success, partial_success, or error execution status.
msg (str): Human-readable execution summary.
output_dir (str): Unique run directory under tool_result/hdock_tool_result.
receptor (str): Resolved receptor input path.
ligand (str): Resolved ligand input path.
nmax (int): Effective model count upper bound used.
no_complex (bool): Effective no-complex flag used.
angle (int): Effective angle parameter used.
rsite (str|None): Effective receptor site file used.
lsite (str|None): Effective ligand site file used.
output_files (dict): Key generated file paths such as Hdock.out, topN.pdb, and best models.
partner_chains (List[str]): Partner chain IDs present in generated complex models. For protein-peptide complexes, pass output_files["best_model_pdb"] and partner_chains[0] to interaction_visualizer(mode="peptide").
metrics (dict): Summary metrics including generated model count and best docking score 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.
- 6d ago First seen · 105 lines · 24 tokens per session scan A 64c7f0b01759
molclaw-hdock-tool is a skill published in the GitHub repository InternScience/MolClaw (33 stars, last pushed 29d ago), licensed MIT. It adds 24 tokens to every session and 1,090 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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