Databio
Official@databio · University of Virginia
Solving problems in computational biology
Agent Skills by Databio
Showing 10 vetted skills indexed across 1 GitHub repositories.
databiomcp-develop
Configure MCP servers with streamable HTTP transport and Python SDK.
databiopython-unit-testing
Guide writing Python unit tests with pytest fixtures, parametrization, and mocking.
databiopython-cli-testing
Automate Typer/Click CLI testing with CliRunner and pytest fixtures.
databioprogress-logging
Append date-stamped 1-3 sentence summaries to progress.md.
databiodocumentation-writing
Write software documentation using one of four structured types per document.
databioweb-design-style
Apply a universal web design framework with tokens.css, utilities.css, and BEM naming.
databiosmoketest-writing
Automate end-to-end smoke test creation for FastAPI backends with Docker PostgreSQL and TestClient.
databiodatabase-guide
Configure PostgreSQL connections and schema setup for FastAPI projects.
databioanalysis-report
Render quantitative results as plots derived directly from data.
databiodocumentation-evaluator
Audit codebase documentation and generate concrete improvement proposals.
Frequently Asked Questions About Databio
FAQPage SchemaWhat specific tasks can developers perform using Databio's engineering standards?▼
Developers can implement robust FastAPI backends, configure PostgreSQL database schemas, execute comprehensive unit and smoke testing, and apply consistent BEM-based web styling. These standards ensure high-quality codebases through structured documentation audits and standardized testing protocols.
Which technical personas benefit most from these engineering practices?▼
Backend engineers, database administrators, and technical writers benefit from these practices. The framework is designed for teams building data-intensive services who require consistent testing, reliable database connectivity, and high-quality, maintainable documentation standards.
What are the primary dependencies for implementing these testing and database configurations?▼
Implementation requires a FastAPI environment, Docker for containerized PostgreSQL instances, and the Pytest framework for test execution. These components form the core infrastructure for the provided smoke testing and database configuration modules.