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