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auerbachb
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pm-rate-team

Evaluate GitHub contributor metrics and CodeRabbit review outcomes over a configurable time window.

3|1|Updated Feb 28, 2026
Search Tags:#automation#github#coderabbit#code-review#project-management#pull-requests#team-metrics
One-click install
npx skills add https://github.com/auerbachb/claude-code-config --skill pm-rate-team
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pm-rate-team
Source: https://github.com/auerbachb/claude-code-config/tree/main/.claude/skills/pm-rate-team
Command: npx skills add https://github.com/auerbachb/claude-code-config --skill pm-rate-team

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Provides a repeatable, data-driven way to evaluate individual and team contributions over a configurable time window so managers and PMs can understand PR throughput, review cycles, issue activity, and AI review effectiveness without manual aggregation.

Core Features & Use Cases

  • Per-contributor metrics: Counts merged PRs, additions/deletions, average review cycles, issues opened/closed, and reviews given.
  • CR first-pass measurement: Computes CodeRabbit first-pass success rate when coderabbitai[bot] reviews are present.
  • Collaboration insights: Identifies review participation and collaboration patterns for coaching and workload balancing.
  • Use case: Run a two-week evaluation to produce a scannable team report for sprint retrospectives and planning.

Quick Start

Run the pm-rate-team skill with --days 14 to produce a two-week Team Contribution Report.

Frequently Asked Questions about pm-rate-team

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I aggregate GitHub pull request metrics for a team performance review?▼

Aggregating GitHub pull request metrics for a team review requires parsing repository events and PR metadata to count merged PRs, track review cycles, and measure issue throughput. This skill compiles per-contributor data over a configurable time window to generate scannable team reports.

How do I measure CodeRabbit first-pass success rate for merged pull requests?▼

Measuring CodeRabbit first-pass success rate involves parsing coderabbitai[bot] reviews from pull request metadata to compute AI review effectiveness. This skill calculates the first-pass success rate alongside per-contributor metrics when CodeRabbit reviews are present in the repository.

Can I use GitHub CLI data to evaluate developer contribution and review participation?▼

Evaluating developer contribution and review participation with GitHub CLI data requires authenticated gh CLI access to gather and filter repository events. This skill uses CLI access and JSON parsing to analyze individual PR throughput, issues opened, and reviews given.

What is the best way to generate a sprint retrospective report from GitHub repository activity?▼

Generating a sprint retrospective report from GitHub repository activity involves evaluating team contributions over a specific timeframe like a two-week sprint. This skill aggregates PR additions, deletions, and collaboration patterns to produce data-driven insights for planning and coaching.

Does this team metrics tool require any specific GitHub repository permissions?▼

This team metrics tool requires authenticated gh CLI access and JSON parsing capabilities to gather repository events and pull request metadata. You need sufficient GitHub repository permissions to read pull request data, issue throughput, and CodeRabbit bot review comments.

What collaboration insights can I get from analyzing GitHub review cycles?▼

Analyzing GitHub review cycles provides collaboration insights by identifying review participation patterns and average review cycles per contributor. This skill highlights workload balancing and coaching opportunities by tracking who reviewed what across merged pull requests within the evaluation window.

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