coderabbit-adoption-report

name	CodeRabbit Adoption Report
description	Report on CodeRabbit adoption across OpenShift org PRs

CodeRabbit Adoption Report

This skill queries the GitHub search API to measure what percentage of merged PRs in the openshift GitHub organization received comments from the coderabbitai[bot] app.

When to Use This Skill

Use this skill when you need to:

• Measure CodeRabbit adoption rates across the openshift org
• Identify repos with high or low CodeRabbit usage
• Generate adoption reports for stakeholders
• Track adoption trends over time

Prerequisites

1. GitHub CLI (gh): Must be installed and authenticated with access to the openshift org.

   gh auth status
   

2. Python 3: Python 3.6 or later is required.

Implementation Steps

Step 1: Verify Prerequisites

gh auth status
python3 --version

Step 2: Run the Script

The script is located at:

plugins/teams/skills/coderabbit-adoption/coderabbit_adoption.py

Execute with appropriate arguments:

# Default: last 30 days, org-wide summary only (2 API calls)
python3 plugins/teams/skills/coderabbit-adoption/coderabbit_adoption.py

# Specific date range
python3 plugins/teams/skills/coderabbit-adoption/coderabbit_adoption.py \
  --start-date 2026-02-01 --end-date 2026-02-28

# Detailed mode: per-repo breakdowns (~50 API calls, prone to rate limiting)
# ONLY use when user explicitly requests --detailed
python3 plugins/teams/skills/coderabbit-adoption/coderabbit_adoption.py --detailed

Step 3: Parse the Output

The script outputs JSON to stdout with the following structure:

Default mode (2 API calls, no per-repo data):

{
  "start_date": "2026-02-04",
  "end_date": "2026-03-06",
  "total_merged_prs": 7950,
  "prs_with_coderabbit": 1445,
  "adoption_pct": 18.2,
  "detailed": false,
  "repo_breakdown": [],
  "no_coderabbit_activity": []
}

Detailed mode (~50 API calls, with per-repo data):

{
  "start_date": "2026-02-04",
  "end_date": "2026-03-06",
  "total_merged_prs": 7950,
  "prs_with_coderabbit": 1445,
  "adoption_pct": 18.2,
  "detailed": true,
  "per_repo_approximate": true,
  "repo_breakdown": [
    {
      "repo": "openshift/cincinnati-graph-data",
      "cr_count": 150,
      "total": 196,
      "adoption_pct": 76.5
    }
  ],
  "no_coderabbit_activity": [
    {
      "repo": "openshift/release",
      "total": 1072
    }
  ]
}

Field Descriptions:

• start_date, end_date: The date range queried
• total_merged_prs: Total merged PRs in the openshift org
• prs_with_coderabbit: PRs where coderabbitai[bot] commented
• adoption_pct: Overall adoption percentage
• detailed: Whether detailed mode was used
• per_repo_approximate: (detailed only) True if per-repo breakdown is approximate (>1000 CodeRabbit PRs)
• repo_breakdown: (detailed only) Array of top repos sorted by CR count descending
• no_coderabbit_activity: (detailed only) High-volume repos with zero CodeRabbit comments

Step 4: Format and Present the Report

• Default mode: Present the summary stats (total PRs, CodeRabbit PRs, adoption %)
• Detailed mode: Also include per-repo table and no-activity list

Step 5: AI Analysis

After presenting the data, provide:

• License gap analysis: repos in repo_breakdown are enabled; missing reviews = engineers without licenses
• Observations on adoption trends
• In default mode, mention --detailed is available but warn it is prone to GitHub API rate limits

Notes

• API usage: Default mode uses only 2 API calls. --detailed makes ~50 calls with 2-second sleeps between each to respect GitHub's search API rate limit (30 requests/minute). Even with throttling, --detailed may hit rate limits and takes several minutes.
• The script uses gh CLI with -X GET for all GitHub API calls (required for the search endpoint)
• Uses Python's standard library only (no external dependencies)
• Diagnostic messages go to stderr, JSON data to stdout
• Never use --detailed unless the user explicitly asks for it