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ClinPGx Database Access

clinpgx-database

K-Dense-AI/claude-scientific-skills

Provide REST API access to ClinPGx, the successor to PharmGKB, for querying gene-drug interactions, CPIC/DPWG/FDA guidelines, allele functions, and evidence that supports precision dosing and pharmacogenomics-driven clinical decisions.

KEGG REST Toolkit

K-Dense-AI/claude-scientific-skills

Direct Python helpers for KEGG's REST API, covering database metadata, listing, search, retrieval, ID conversion, linkage, and drug interactions to power pathway and gene analysis.

Advanced Molecular Control

K-Dense-AI/claude-scientific-skills

RDKit delivers a Python-based cheminformatics toolkit for parsing SMILES/SDF, computing descriptors, generating 2D/3D coordinates, fingerprinting, searching substructures, managing reactions, and visualizing molecules, ideal for drug discovery and computational chemistry workflows.

Reactome Pathway Explorer

reactome-database

K-Dense-AI/claude-scientific-skills

Query the Reactome Content and Analysis Services (or the reactome2py client) to fetch pathway hierarchies, map genes, run overrepresentation/expression analyses, and explore disease interactions for systems biology research.

Automated AI Data Scraping Agent

data-scraper-agent

affaan-m/everything-claude-code

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

Structured Knowledge Extraction From AI Models

bdistill-knowledge-extraction

sickn33/antigravity-awesome-skills

bdistill transforms AI interactions into a structured, queryable knowledge base. It extracts, structures, and quality-scores domain knowledge from both closed-source AI models (in-session) and local open-source models (via Ollama). Users can build comprehensive reference datasets, Q&A pairs, or generate structured training data for traditional machine learning, ensuring validated and exportable domain expertise.

Power BI Performance Triage

power-bi-performance-troubleshooting

github/awesome-copilot

Provides systematic Power BI performance troubleshooting guidance covering model optimization, DAX design, report layout, and capacity diagnostics, plus tool-driven measurement tips for faster page loads, interactions, and query execution.

Segment Automation Toolkit

segment-automation

sickn33/antigravity-awesome-skills

Orchestrate Segment customer-data actions through Rube MCP and Composio, covering event tracking, user identification, grouping, page views, batch dispatches, alias merges, and source management while always refreshing schema info first.

DepMap Cancer Dependency Analysis Tool

K-Dense-AI/scientific-agent-skills

This skill provides programmatic access to the Cancer Dependency Map (DepMap), a comprehensive resource characterizing genetic dependencies in cancer cell lines. Use it to identify genes essential for specific cancer types, discover synthetic lethal interactions, and validate potential oncology drug targets using CRISPR and RNAi data.

SHAP Model Interpretability and Explainability

K-Dense-AI/scientific-agent-skills

SHAP (SHapley Additive exPlanations) provides a unified, robust framework for understanding complex machine learning models. It calculates feature importance using Shapley values from game theory, allowing users to interpret individual predictions, analyze model bias, visualize feature interactions, and debug model behavior. Applicable across deep learning, tree-based, and black-box models.

SimPy: Discrete Event Simulation Framework

K-Dense-AI/scientific-agent-skills

SimPy is a powerful, process-based discrete-event simulation framework written in Python. It enables users to model complex systems involving processes, shared resources, queues, and time-based interactions. It is ideal for analyzing manufacturing lines, network traffic, logistics, or service operations where resource contention and irregular, time-based events are key factors.

Hex CI/CD Integration Guide

hex-ci-integration

jeremylongshore/claude-code-plugins-plus-skills

This skill guides the setup of CI/CD pipelines for Hex data analytics projects using GitHub Actions. It enables running automated unit tests on pull requests and triggering live project runs on the main branch merge. Use this when establishing automated testing workflows, validating data transformation logic, or integrating Hex outputs into a continuous delivery process.

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