code-quality-docs

name	code-quality-docs
description	Apply comment and documentation standards for Python code. Use when writing docstrings, adding comments, or marking technical debt (TODOs). Ensures explain-why-not-what and traceable debt.

Code Quality: Documentation and Comments

Comments explain why, not what. Code should be self-documenting.

Docstrings

• Write the docstring before implementation. If you cannot summarize in one sentence, the design is not clear yet.
• Complete docstrings for public and core functions: Args, Returns, Raises, and examples for complex functions. Follow your project's function-definition rules (often under .cursor/rules/).
• Explain non-obvious decisions. If a threshold, chunk size, or algorithm was chosen for a specific reason (benchmark, compliance, environment limit), document it.

Module and package docstrings (scripts and tooling)

For CLI modules, data pipelines, and agent-facing packages, a one-line file header is usually not enough. Prefer a short block at the top of *.py that covers:

• Purpose — what problem the module solves and who it is for (human vs automation).
• Processing — the main steps, inputs, and outputs in order (not a wall of prose).
• Boundaries — what is explicitly out of scope, or where personal/sensitive data is expected to live (e.g. gitignored paths).

Function and method docstrings can then stay focused on contracts (Args / Returns / Raises). Dutch (or other) UI strings are fine in user-facing text; keep identifiers and public API names in English.

Comments

• Do not comment what the code already says. Remove noise.
• Explain why when the reason is not obvious from code alone.

Technical Debt (TODOs)

• Prefer task reference: # TODO(TASK-NNN): … or # TODO(#123): … when your repo issues map that way
• Alternative: One SMART sentence when no task exists yet: unambiguous, actionable, discoverable

Never use a bare # TODO without either a task ID or a complete, self-contained description.