rory-data
@rory-data
Public Skills
skill-creator
by rory-data
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends the Agent's capabilities with specialised knowledge, workflows, or tool integrations.
airflow
by rory-data
Manages Apache Airflow operations including listing, testing, running, and debugging DAGs, viewing task logs, checking connections and variables, and monitoring system health. Use when working with Airflow DAGs, pipelines, workflows, or tasks, or when the user mentions testing dags, running pipelines, debugging workflows, dag failures, task errors, dag status, pipeline status, list dags, show connections, check variables, or airflow health.
docker-best-practices
by rory-data
Docker and container image best practices including multi-stage builds, security hardening, layer optimization, and Alpine/slim variants. Use when writing or reviewing Dockerfiles, container configurations, or docker-compose files.
authoring-dags
by rory-data
Workflow and best practices for writing Apache Airflow DAGs. Use when the user wants to create a new DAG, write pipeline code, or asks about DAG patterns and conventions. For testing and debugging DAGs, see the testing-dags skill.
golang-conventions
by rory-data
Go coding standards for Go 1.21+, including idioms, error handling, testing patterns, concurrency, and golangci-lint configuration. Use when writing, reviewing, or refactoring Go code, working with goroutines, or setting up Go projects.
debugging-dags
by rory-data
Comprehensive DAG failure diagnosis and root cause analysis. Use for complex debugging requests requiring deep investigation like "diagnose and fix the pipeline", "full root cause analysis", "why is this failing and how to prevent it". For simple debugging ("why did dag fail", "show logs"), the airflow entrypoint skill handles it directly. This skill provides structured investigation and prevention recommendations.
managing-astro-local-env
by rory-data
Manage local Airflow environment with Astro CLI. Use when the user wants to start, stop, or restart Airflow, view logs, troubleshoot containers, or fix environment issues. For project setup, see setting-up-astro-project.
markdown-conventions
by rory-data
Documentation and content creation standards for Markdown files. Use when writing, reviewing, or formatting Markdown documentation, README files, or technical content.
python-testing-patterns
by rory-data
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
principal-data-engineer
by rory-data
Expert-level guidance on data platform architecture, pipeline design patterns, and engineering rigor. Use when designing data platforms, reviewing Airflow DAGs, working with Polars/DuckDB/dbt, establishing data quality contracts, implementing composable data stacks, or architecting lakehouse solutions with Iceberg.
testing-dags
by rory-data
Complex DAG testing workflows with debugging and fixing cycles. Use for multi-step testing requests like "test this dag and fix it if it fails", "test and debug", "run the pipeline and troubleshoot issues". For simple test requests ("test dag", "run dag"), the airflow entrypoint skill handles it directly. This skill is for iterative test-debug-fix cycles.
python-conventions
by rory-data
Python coding standards including PEP 8, type hints, modern syntax (3.11+), ruff formatting, uv package management, and best practices. Use when writing, reviewing, or refactoring Python code, setting up Python projects, or managing dependencies.