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-prolif-dockinggit 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-docking)<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-prolif-docking"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-prolif-docking/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-prolif-docking"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-prolif-docking.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 | $0.00025 | $0.01099 |
| Opus 5.5 | $0.00010 | $0.00440 |
| Sonnet 5.5 | $0.00005 | $0.00220 |
| Haiku 4.5 | $0.00003 | $0.00110 |
Grade A, and why
molclaw-prolif-docking 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ProLIF Docking Pose Analysis Skill
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.
[!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.
Task Description
Batch-analyze multiple docking-generated binding poses and produce interaction fingerprints or interaction count summaries. Use this skill to screen binding modes and evaluate docking result quality.
Routing note: This tool is the primary choice for batch docking fingerprint comparison (≥ 2 poses). For single-structure deep analysis (one pose, one complex), use
molclaw-interaction-visualizerinstead — it provides Schrödinger-style 2D diagrams, PyMOL 3D renderings, and decision-ready JSON that this tool does not produce.
Input Source Mapping
| Parameter | Source Guidance |
|---|---|
protein_path |
Generated by structure retrieval/prediction tools (e.g., retrieve_protein_structure_by_*, pred_protein_structure_esmfold, chai1_predict) or a PDB fixed by fix_pdb |
ligand_paths |
Generated by docking tools (e.g., molecule_docking_quickvina_fullprocess, hdock_tool, karmadock_tool) as pose files (.sdf/.mol2/.pdbqt) |
ligand_format |
Must match the upstream docking output format: sdf, mol2, or pdbqt |
template_smiles |
Required when ligand_format is pdbqt to provide ligand chemistry reference |
Usage
Tool: prolif_docking
Summarize docking poses with ProLIF and return a CSV of interaction fingerprints plus summary metrics.
Args:
protein_path (str): Path to the receptor protein structure.
ligand_paths (List[str]): List of ligand pose files.
ligand_format (str): Ligand format identifier (e.g., 'sdf', 'mol2', 'pdbqt').
template_smiles (str|None): Optional template SMILES; required when ligand_format is 'pdbqt'.
interactions (List[str]|None): Optional interaction types to compute.
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.
Return:
status (str): 'success' or 'error'.
msg (str): Human-readable summary or error message.
command (str): The executed command label ('docking').
output_dir (str|None): Run-specific directory under tool_result/prolif_result.
output_file (str|None): Path to the produced CSV summary file.
n_frames (int|None): Number of processed frames where applicable.
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.
- 1mo ago First seen · 103 lines · 25 tokens per session scan A 82cf4f248a5b
molclaw-prolif-docking is a skill published in the GitHub repository InternScience/MolClaw (38 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 1,099 once invoked, about $0.0001 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.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Builds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein…
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
presenting-conference-talks
Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral talks, spotlight presentations, or invited talks for ML and systems conferences.