code-suggest-commit

To generate conventional commit messages from git diffs, analyze the changes and context to produce descriptive subjects aligned with repository conventions. This ensures consistent history and reduces guesswork when summarizing code reviews or feature updates.

Writing commit messages for multi-file changes works best by analyzing the diff to craft precise, descriptive messages. When changes span multiple concerns, it recommends splitting them into separate commits and suggests appropriate subject lines for each.

You can use AI to suggest commit messages that match project guidelines by analyzing existing patterns and diffs. It provides one or more conventional commit options aligned with repository conventions, ensuring messages follow project-specific formatting rules.

You should split changes into multiple commits when a single diff spans multiple concerns. Analyzing the code changes helps identify distinct logical units, allowing you to structure separate, precise commit messages for each feature update or modification.

Generating commit messages during code reviews works by analyzing the diff and context to craft conventional, clear messages. It applies to code review scenarios, feature updates, and multi-file changes, ensuring descriptive and precise summaries.