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databio AI Skills

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Browse published AI skills maintained by databio. Compare skill descriptions and follow each source repository for setup instructions.

Author statistics

Indexed skills

5

Repository stars across indexed skills

5

Repository forks

0

Average repository stars per indexed skill

1

Repository stars may repeat across skills from the same repository.

5 skills

Browse skills

GitHub

progress-logging

databio

Record session progress to progress.md with date-stamped entries (YYYY-MM-DD format) containing 1-3 sentence summaries. Focuses on outcomes not process, using action verbs like Created, Implemented, Fixed, Refa...

GitHub

analysis-report

databio

Write data analysis reports where all quantitative information appears in programmatically-generated plots, never in hand-written text tables. Prevents AI from fabricating numbers by ensuring all values come fr...

GitHub

documentation-writing

databio

Write documentation using the four-types system (Tutorial, How-to, Reference, Explanation). Each type serves a distinct purpose - don't mix them. Use when creating docs, README files, guides, or any technical w...

GitHub

smoketest-writing

databio

Write isolated integration/smoke tests for FastAPI backends using ephemeral Docker PostgreSQL, TestClient, and dependency injection. Tests run against temporary database (not dev DB), gated by RUN_INTEGRATION_T...

GitHub

python-unit-testing

databio

Write Python unit tests using pytest. Tests should be non-trivial, complete in under 30 seconds, and run with just "pytest". Covers conftest.py fixtures, test organization, parametrization, mocking, and tempora...

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.