ai-settings

Generating release notes from a git diff involves parsing the current diff and changed files to produce structured, deterministic artifacts. A mode-driven analysis tool reads this diff context to output standardized reports suitable for downstream delivery workflows.

Mode-driven git diff analysis is the process of parsing diff context and changed files to produce deterministic outputs for specific delivery stages. It supports multiple modes including release notes, acceptance criteria, repo style alignment, unit-test opportunities, and pre-commit checks.

Extracting acceptance criteria from a git diff requires loading the appropriate mode and gathering pre-work diff context. The process reads changed files to generate a targeted, deterministic artifact that satisfies specific delivery quality requirements.

Yes, you can automate pre-commit checks by parsing arguments for the pre-commit mode and analyzing the current git diff. This generates deterministic outputs that function as CI checks to enforce delivery quality standards before changes are committed.

Yes, this mode-driven git diff analysis specifically solves the problem of producing structured output for ETNA_TRADER delivery quality. It analyzes current diffs and changed files to generate standardized artifacts tailored to the ETNA_TRADER platform's downstream tasks.

Identifying unit test opportunities from changed files involves selecting the unit-test mode and reading the current git diff. The analysis generates deterministic artifacts that highlight specific areas within the changed code that require test coverage.