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Verwandte Berufe SOC
Basierend auf der SOC-Berufsklassifikation
name github-analysis description Analyze GitHub commits, generate PR reviews, calculate contributor leaderboards, and assess code quality. Use when analyzing git commits, reviewing code, generating GitHub activity reports, or tracking developer contributions.
GitHub Analysis
Analyze GitHub activity, review code, and track contributions.
Quick Start
Analyze commits from JSON file:
python scripts/analyze_commits.py commits.json
Generate leaderboard:
python scripts/calculate_leaderboard.py commits.json --period week
Commit Analysis
What to Extract
From each commit, analyze:
Author & timestamp Commit message quality
Clear (explains what and why)
Vague (just what, no why)
Cryptic (no context)
Files changed (count and types)Lines added/removed Code quality indicators
TODOs added
FIXMEs added
Console.log/debugging code
Commented code
Large file changes (>500 lines)
Quality Scoring
Commit Message Quality:
Excellent (8-10): Clear what + why, follows conventions
Good (5-7): Clear what, some context
Poor (1-4): Vague or no context
Bad (0): Single word, "wip", "test"
Code Quality Indicators:
grep -r "console.log\|debugger\|print(" changed_files/
"TODO\|FIXME"
wc
"^[[:space:]]*//.*=\|^[[:space:]]*/\*"
PR Review Template Use this structure for code reviews:
# Pull Request Review
## Summary
[1-2 sentence overview of changes]
## Code Quality Assessment
### Structure & Organization
- ✅ **Good** : Well-organized, clear separation of concerns
- ⚠️ **Needs Work** : Mixed responsibilities, unclear structure
- 🔴 **Issues** : Significant structural problems
### Naming & Readability
- **Variables** : [clear/unclear/inconsistent]
- **Functions** : [descriptive/vague/confusing]
- **Comments** : [helpful/missing/outdated]
### Testing
- [ ] Unit tests included
- [ ] Integration tests updated
- [ ] Edge cases covered
- [ ] Test coverage: [%]
## Issues Found
### 🔴 Critical
- [Issue with security/correctness impact]
### 🟡 Warnings
- [Issue that should be addressed]
### 🔵 Suggestions
- [Nice-to-have improvements]
## Security Check
- [ ] No hardcoded credentials
- [ ] No SQL injection risks
- [ ] No XSS vulnerabilities
- [ ] Input validation present
- [ ] Authentication/authorization correct
## Performance
- [ ] No obvious performance issues
- [ ] Database queries optimized
- [ ] No N+1 query problems
- [ ] Appropriate caching
## Recommendations
1. [Priority recommendation]
2. [Additional improvement]
3. [Nice-to-have enhancement]
## Verdict
- [ ] ✅ **Approve** - Ready to merge
- [ ] 🟡 **Approve with Comments** - Minor issues, can merge
- [ ] 🔴 **Request Changes** - Must address issues before merge
Contributor Leaderboard
Metrics Track these metrics per contributor:
Commit Count (weight: 1x)Lines Changed (weight: 0.5x)
Added lines + modified lines
Commit Quality (weight: 2x)
Average message quality score
PR Reviews (weight: 1.5x)
Number of PR reviews contributed
Response Time (weight: 1x)
Average time to respond to PR comments
Scoring Formula Total Score = (commits × 1) +
(lines_changed / 100 × 0.5) +
(avg_quality × 2) +
(pr_reviews × 1.5) +
(10 - avg_response_hours × 1)
Leaderboard Format # GitHub Contributor Leaderboard
## Period: [Week/Month]
| Rank | Contributor | Score | Commits | Lines | Quality | Reviews |
|------|-------------|-------|---------|-------|---------|---------|
| 1 | John Doe | 45.2 | 12 | 1,234 | 8.5 | 5 |
| 2 | Jane Smith | 38.7 | 10 | 987 | 7.8 | 4 |
Code Quality Metrics
Complexity Analysis
grep -n "function\|def " file.js | while read line; do
done
Code Churn Files with high churn (changed frequently):
git log --format=format: --name-only | \
sort | uniq -c | sort -rn | head -20
Unstable code
Unclear requirements
Technical debt
Active development area
Test Coverage
npm test -- --coverage
python -m pytest --cov=src tests/
Critical paths: 90%+
Business logic: 80%+
Overall: 70%+
Data Processing
Input Format (commits.json) [
{
"sha" : "abc123" ,
"author" : "John Doe" ,
"email" : "john@example.com" ,
"date" : "2026-01-04T10:30:00Z" ,
"message" : "Add user authentication feature" ,
"files_changed" : [ "src/auth.js" , "src/users.js" ] ,
"additions" : 125 ,
"deletions" : 45 ,
"files_count" : 2
}
]
Output Format (analysis.json) {
"summary" : {
"total_commits" : 25 ,
"total_contributors" : 5 ,
"total_files_changed" : 67 ,
"total_lines" : 2345
} ,
"contributors" : [
{
"name" : "John Doe" ,
"commits" : 12 ,
"lines_changed" : 1234 ,
"avg_quality" : 8.5 ,
"score" : 45.2
}
] ,
"hot_files" : [
{ "file" : "src/auth.js" , "changes" : 8 }
] ,
"quality_issues" : [
{ "type" : "TODO" , "count" : 5 } ,
{ "type" : "console.log" , "count" : 3 }
]
}
Scripts
analyze_commits.py Analyzes commit data and generates metrics.
python scripts/analyze_commits.py input.json --output analysis.json
calculate_leaderboard.py Calculates contributor rankings.
python scripts/calculate_leaderboard.py commits.json \
--period week \
--output leaderboard.json
generate_report.py Generates HTML report from analysis.
python scripts/generate_report.py analysis.json \
--template github-summary \
--output report.html
Integration with Agents
Code Agent
commits = github.get_commits(repo='owner/repo' , days=7 )
python scripts/analyze_commits.py commits.json
Reporting Agent
python scripts/calculate_leaderboard.py commits.json
python scripts/generate_report.py analysis.json --template github-summary
Reference Files 