Agent Skills Hub

agentdb-state-manager

Persistent state management and workflow analytics using DuckDB for task dependency tracking, historical metrics, and context checkpointing.

senior-data-engineer

World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.

FastMCP Development

Build and manage MCP servers using the FastMCP framework. Guide for creating tools, resources, prompts, Claude Desktop integration, and deployment with Python and TypeScript.

molthouse

API-first casino for AI agents on Base. Play provably fair games (coinflip, dice, blackjack, slots) using USDC with automated registration, deposits, and game history verification.

single-cell-rna-qc

Automated single-cell RNA-seq quality control pipeline following scverse best practices. Performs MAD-based outlier detection, cell filtering, and diagnostic visualization for .h5ad and .h5 datasets.

serena-mcp

Semantic code analysis guide for Serena MCP. Automatically prioritizes Serena tools for symbols, references, and code memory to optimize context and efficiency.

paperbanana

Generate publication-quality statistical plots from CSV or JSON data files using AI-driven automated visualization.

skill-architect

Expert consultant for designing and building high-quality, consistent AI agent skills. Guides you through discovery, architecture, and creation phases to ensure reliable, composable, and efficient skill delivery.

perf-analyzer

Synthesize performance profiling data into actionable recommendations and evidence-backed technical decisions.

image-generation

Generate high-quality visual content, characters, and scenes using structured JSON prompts and automated Python execution for guided image synthesis.

dotnet-claude-code-skills

A suite of .NET engineering skills for Domain-Driven Design (DDD), EF Core persistence, BDD-style unit testing, and IDE-like semantic code understanding with Serena MCP.

guard

Epistemic safety analysis for JSON data in prompts to prevent LLM hallucinations and reasoning errors when handling incomplete or large-scale datasets.