Agent Skills Hub

debugging

Standardized debugging and diagnostic guidelines for AI coding agents.

backend-development

Build, optimize, and maintain production-ready backend systems using Node.js, Python, Go, and Rust. Includes API design, database management, security, and DevOps best practices.

issue-resolver

Automated GitHub issue analysis, triage, and resolution planning tool integrated with Specification Driven Development (SDD) workflows.

clean-code

Pragmatic AI-assisted coding standards focused on clean code, simplicity, and maintainability. Enforces best practices like SRP, DRY, and KISS to prevent over-engineering.

data-cleaning-pipeline-generator

Generates data cleaning pipelines for pandas/polars/PySpark, handling missing values, duplicates, outliers, type conversions, and validation.

test-generation

Intelligent unit and integration test generation powered by Minion framework, featuring business logic validation, boundary testing, and Vitest integration.

rust-developer

Expert Rust development guide based on real-world code reviews. Ideal for idiomatic code, performance tuning, error handling, and avoiding common pitfalls in CLI and production tools.

moai-lang-c

C programming language expert for memory management, systems programming, low-level optimization, and debugging best practices.

moai-essentials-debug

Advanced multi-language debugging support with stack trace analysis, runtime error triage, and automated diagnostic tools for containerized and distributed systems.

core-dev

Development guide for lemline-core, the stateless Serverless Workflow engine. Manage workflow execution, node navigation, state transitions, JQ expression evaluation, error handling, and parallel fork logic.

coding-aider-plan-generator

Generate structured development plans, checklists, and file contexts compatible with the IntelliJ coding-aider plugin.

data-analysis

Data Analysis Specialist for EDA, statistical modeling, SQL queries, and Python-based visualization. Turn raw datasets into actionable insights through rigorous quantitative methods.