my-eca-config

Use when a user asks what Code Health means, how to interpret scores, or why Code Health matters in daily development.

Use when refactoring unhealthy code and needing Code Health findings to choose small safe steps and verify improvement.

Use when a user asks for ROI, stakeholder justification, delivery impact, or defect-risk reduction from improving Code Health in a file.

Use when AI-generated or AI-modified changes need a Code Health gate before commit, handoff, or pull request.

Run linting and unit tests against the current repository, auto-discovering the correct commands from Justfile, Makefile, pyproject.toml, or package.json.

Create a conventional commit from staged changes, with a diff-derived description body.

Reliably obtain a non-empty unified git diff for the current branch using safe fallbacks (origin/HEAD...HEAD, origin/main...HEAD, origin/master...HEAD) and return structured JSON containing the diff and the command used.

Produce an implementation plan with a functional-leaning, idiomatic style mindset; prefers lightweight data structures over dataclasses/pydantic unless justified.

Coding style policy for generated code: prefer idiomatic language conventions with a functional-leaning approach (pure-ish functions, composability), and prefer lightweight data structures over heavy schema/class abstractions unless clearly justified.