Analysis

Use this skill for hands-on scientific work that transforms data or code context into interpretable intermediate artifacts.

When To Use

1. Inspecting or transforming astronomy data products.
2. Drafting or revising notebook and Python analysis code.
3. Producing exploratory plots, tables, or simulation setup notes.
4. Interpreting intermediate results before they are treated as validated findings.

Inputs

1. Data products, notebook context, or source files.
2. Units, coordinate system, instrument metadata, and provenance details.
3. Desired artifact, such as a plot, summary table, or analysis note.

Procedure

1. Confirm the input data source, units, coordinate frame, and intended output.
2. State the assumptions needed to proceed, especially where provenance or calibration is incomplete.
3. Produce the smallest useful analysis artifact first, such as a derived table, plot, or code patch.
4. Label the result as exploratory unless validation criteria are explicitly met.