economic-data-project

Data-first visualization design combining Tufte principles with Jobs/Ive simplicity for React + Nivo dashboards.

Automated agent workflow for reviewing and updating project agent context files when code changes are made.

Create a custom Dagster Component with demo mode support, realistic asset structure, and optional custom scaffolder using the dg CLI. Use this skill if there is no Component included in an existing integration or if Dagster does not have the integration.

Expert guidance for Dagster data orchestration including assets, resources, schedules, sensors, partitions, testing, and ETL patterns. Use when building or extending Dagster projects, writing assets, configuring automation, or integrating with dbt/dlt/Sling.

Expert guidance for working with Dagster and the dg CLI. ALWAYS use before doing any task that requires knowledge specific to Dagster, or that references assets, materialization, components, data tools or data pipelines. Common tasks may include creating a new project, adding new definitions, understanding the current project structure, answering general questions about the codebase (finding asset, schedule, sensor, component or job definitions), debugging issues, or providing deep information about a specific Dagster concept.

Initialize a dagster project using the create-dagster cli. Create a dagster project, uv virtual environment, and everything needed for a user to run dg dev or dg check defs successfully. (project)

Production Python coding standards with automatic version detection (3.10-3.13). Use when writing, reviewing, or refactoring Python to ensure adherence to modern type syntax, LBYL exception handling, pathlib operations, ABC-based interfaces, and production-tested patterns. Not Dagster-specific - applies to any Python project.

Standardize Docker/Dagster environment debugging and recovery workflows.

Automates the complete git and GitHub workflow: initializes a git repository, creates a private GitHub repository if needed, commits changes, creates a pull request, monitors GitHub Actions for completion, and merges the PR if all checks pass.

General-purpose GitHub exploration and analysis tool for searching issues, creating PRs, analyzing git history, and reviewing PR comments

This skill should be used when editing Python code in the erk codebase. Use when writing, reviewing, or refactoring Python to ensure adherence to LBYL exception handling patterns, Python 3.13+ type syntax (list[str], str | None), pathlib operations, ABC-based interfaces, absolute imports, and explicit error boundaries at CLI level. Also provides production-tested code smell patterns from Dagster Labs for API design, parameter complexity, and code organization. Essential for maintaining erk's dignified Python standards.

React component patterns, hooks, and state management for data visualization dashboards

Automate issue triage, planning, and branch creation for issue-driven development.

Tailwind CSS configurations and patterns for building data-dense financial dashboard UIs

Comprehensive testing patterns and examples for Dagster, dbt, FastAPI, and React in the economic data project.

Type-safe data modeling patterns for financial and economic data visualization applications

Automated agent that reviews and updates all Claude context files when code changes are made

Expert guidance for Dagster data orchestration including assets, resources, schedules, sensors, partitions, testing, and ETL patterns. Use when building or extending Dagster projects, writing assets, configuring automation, or integrating with dbt/dlt/Sling.

Initialize a dagster project using the create-dagster cli. Create a dagster project, uv virtual environment, and everything needed for a user to run dg dev or dg check defs successfully. (project)

Production Python coding standards with automatic version detection (3.10-3.13). Use when writing, reviewing, or refactoring Python to ensure adherence to modern type syntax, LBYL exception handling, pathlib operations, ABC-based interfaces, and production-tested patterns. Not Dagster-specific - applies to any Python project.

Automates the complete git and GitHub workflow: initializes a git repository, creates a private GitHub repository if needed, commits changes, creates a pull request, monitors GitHub Actions for completion, and merges the PR if all checks pass.

General-purpose GitHub exploration and analysis tool for searching issues, creating PRs, analyzing git history, and reviewing PR comments

This skill should be used when editing Python code in the erk codebase. Use when writing, reviewing, or refactoring Python to ensure adherence to LBYL exception handling patterns, Python 3.13+ type syntax (list[str], str | None), pathlib operations, ABC-based interfaces, absolute imports, and explicit error boundaries at CLI level. Also provides production-tested code smell patterns from Dagster Labs for API design, parameter complexity, and code organization. Essential for maintaining erk's dignified Python standards.

React component patterns, hooks, and state management for data visualization dashboards

Tailwind CSS configurations and patterns for building data-dense financial dashboard UIs

Comprehensive testing patterns and examples for Dagster, dbt, FastAPI, and React in the economic data project.

Type-safe data modeling patterns for financial and economic data visualization applications