Network Tox Docking Research Planner

Generates four-tier network toxicology and molecular docking research plans from a toxicant and disease input, detailing targets, pathways, docking, workflow...

This skill is instruction-only and appears coherent for designing network toxicology + docking studies. Before using it: (1) recognize that any docking recommendations that require online servers (e.g., CB‑Dock2) will typically involve uploading molecular structures — avoid uploading proprietary or unpublished compounds if you need confidentiality; (2) treat the outputs as planning guidance, not executed analyses — the skill will recommend datasets and tools but does not run them; (3) be cautious about literature citations or curated targets the assistant provides — verify PubMed citations and any 'manually curated' targets because the model can hallucinate sources; (4) if you expect automated execution (fetching datasets, running docking), confirm the platform/tooling used will actually perform those actions and respects data-handling policies; (5) if you need to keep data private, plan to run recommended analyses locally or on trusted infrastructure rather than using public web services.

Type: OpenClaw Skill Name: network-tox-docking-research-planner Version: 0.1.0 The bundle is a research planning tool designed to guide an AI agent in generating scientific study designs for network toxicology and molecular docking. The instructions in SKILL.md and the reference files (modules.md, study-patterns.md) focus entirely on legitimate bioinformatics workflows, such as retrieving data from public databases (PubChem, GeneCards, STRING) and outlining computational analysis steps. There is no evidence of malicious intent, data exfiltration, or harmful prompt injection; rather, the instructions include rigorous scientific constraints, such as warning against overinterpreting docking results and providing fallback logic for low-data scenarios.