Does this tool work with new, uncommitted code?

Yes, the skill includes an 'uncommitted' mode that analyzes staged and unstaged changes in your working directory against the current HEAD.

Can I integrate the output into other tools?

Absolutely. The helper script provides a JSON output mode specifically designed for machine readability and integration into other developer tools or scripts.

How does the Suggest Reviewers Helper identify authors?

The skill uses a Python script to parse git diffs for modified line ranges and then runs a targeted git blame on those specific lines to identify the original authors.

Will it suggest bot accounts as reviewers?

No, the script includes a filtering engine that automatically removes common bots like Dependabot, Renovate, and various CI robots based on name patterns.

Suggest Reviewers Helper

Name: Suggest Reviewers Helper
Author: openshift-eng

byopenshift-eng

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Collaboration Tools

Identifies the best code reviewers by analyzing git blame data for specific line changes and filtering out bot accounts.

About

This skill provides a specialized Python helper script designed to streamline the code review process within git-based workflows. By performing targeted git blame analysis on only the lines that have been modified—rather than entire files—it identifies the most relevant subject matter experts for a specific set of changes. The tool aggregates contribution statistics, identifies the most recent authors, and automatically filters out common CI and bot accounts, making it an essential utility for developers looking to automate and optimize the /git:suggest-reviewers command in Claude Code.

Key Features

Targeted blame analysis restricted to modified line ranges for high performance
Dual output formats in machine-readable JSON or human-readable text
Aggregated statistics including line counts, contribution dates, and author emails
Automatic filtering of GitHub bots, CI robots, and generic bot patterns
29 GitHub stars
Support for both uncommitted (staged/unstaged) and committed feature branch changes

Use Cases

Routing developer questions to the most recent contributors of a file
Identifying subject matter experts for specific legacy code blocks
Automating the selection of code reviewers for complex pull requests

About

Key Features

Targeted blame analysis restricted to modified line ranges for high performance
Dual output formats in machine-readable JSON or human-readable text
Aggregated statistics including line counts, contribution dates, and author emails
Automatic filtering of GitHub bots, CI robots, and generic bot patterns
29 GitHub stars
Support for both uncommitted (staged/unstaged) and committed feature branch changes

Use Cases

Routing developer questions to the most recent contributors of a file
Identifying subject matter experts for specific legacy code blocks
Automating the selection of code reviewers for complex pull requests