causal-inference-guide
Causal inference methods including DiD, IV, RDD, and synthetic control
Causal inference methods including DiD, IV, RDD, and synthetic control
Clinical pharmacology principles for dosing, drug interactions, and patient s...
Computational drug-target interaction prediction and virtual screening
Survey of LLM agents for biomedical scientific discovery
Initial reconnaissance on binaries including checksec, file analysis, strings, and symbols. First step for any new target.
This skill should be used when the user needs to query COSMIC Cancer Gene Census to check if genes are known cancer genes. Triggers include requests to annotate genes with cancer information, check if variants are in cancer genes, or retrieve cancer gene properties from COSMIC database.
Provision brain-computer interface interaction capabilities.
Check if medicinal chemistry papers are in ChEMBL database to access curated bioactivity data
Heme/Onc consultant: Rapid clinical decision support for hematology and oncology with multi-level analysis. Provides immediate guidance followed by deep adversarial validation, tumor board simulation with multiple specialties, evidence-based research, and risk-benefit analysis. Use for diagnostic dilemmas, treatment planning, complex cases, or when uncertain about clinical decisions in hematology/oncology.
Instrument safety checks, content filters, and guardrails for agent outputs
Find and thoroughly read a pathology foundation model paper from the papers/ directory. Use as a prerequisite before adding model information or magnification to the README.
Calculate and add the effective magnification for a pathology foundation model already listed in the README. Use when the user asks to add magnification for a model that is already in the table.
Use when running mutation testing, killing mutants, verifying test quality, checking mutation score, or analyzing survivors after the test baseline is green
Fast high-dimensional fixed effects: OLS, Poisson, IV with multi-way FE; DiD (TWFE, did2s, Sun-Abraham); clustered SEs; etable/coefplot/iplot. Use for FE regressions or DiD. For panel RE/between use linearmodels; for GLM without FE use statsmodels.
Kerberos protocol attack techniques and exploitation
Bug bounty and pentest reconnaissance methodology
Using Density-Fit Correlations in Coot
RDKit molecular manipulation and visualization within Coot's Python environment. Use when working with Coot and need to (1) Create RDKit molecules from Coot monomers, (2) Modify molecular structures (e.g., atom substitution), (3) Generate 2D chemical structure diagrams, (4) Perform cheminformatics operations on ligands or small molecules loaded in Coot.
Comprehensive structure validation combining model-to-map analysis and unmodeled density detection
Best practices for protein structure refinement and validation in Coot. Use when performing (1) Residue refinement operations, (2) Model building and fitting, (3) Rotamer fixing, (4) Scripted/automated refinement workflows, (5) Validation and correlation checking.
Cross-Database Compound Lookup - Cross-reference compound across databases: PubChem, ChEMBL, KEGG, and CAS number lookup. Use this skill for chemical information tasks involving get compound by name get molecule by name kegg find CASToPrice. Combines 4 tools from 4 SCP server(s).