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Abdox-menaraAbdox-menara/guard-skills/skills/workflow/pair-programming/SKILL.md

pair-programming

Skill0 starsChanged 3 months agoMITView on GitHub

ULTRA-ADVANCED Pair Programming - Pair programming workflow - driver/navigator roles, rotation timing, collaboration patterns

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SKILL.md

Pair Programming - ULTRA-ADVANCED v1.0

Overview

Pair programming workflow - driver/navigator roles, rotation timing, collaboration patterns. This skill scans codebases for violations, scores compliance, and generates actionable recommendations.

Detection Patterns

PatternDescriptionSeverity
No role switchingDriver never changes during sessionmedium
Communication gapSilent pairing without discussionmedium
Pace mismatchOne person dominates keyboardmedium
No breaks scheduledToo long without role switchinglow
Tool problemsEnvironment sharing issueslow

Scoring

  • A (90-100): Excellent
  • B (75-89): Good
  • C (60-74): Fair
  • D (40-59): Poor
  • F (0-39): Failing

Implementation

import re, os
from typing import Dict, List, Set, Any
from datetime import datetime

class PairProgramming:
    def __init__(self):
        self.file_results = {}

    def scan_file(self, file_path: str) -> Dict:
        try:
            with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
                content = f.read()
            return self._analyze(content, file_path)
        except Exception as e:
            return {'error': str(e), 'file': file_path}

    def _analyze(self, content: str, file_path: str) -> Dict:
        issues = []
        for pid, info in self._patterns().items():
            matches = re.findall(info['regex'], content, re.IGNORECASE | re.MULTILINE)
            if matches:
                issues.append({'id': pid, 'severity': info['severity'],
                               'count': len(matches), 'message': info['message']})
        score = max(0.0, 100.0 - sum(self._weight(i['severity']) * i['count'] for i in issues))
        return {'file': file_path, 'issues': issues, 'score': round(score, 1),
                 'grade': self._grade(score), 'analyzed_at': datetime.now().isoformat()}

    def _patterns(self) -> Dict:
        return {}

    def _weight(self, s: str) -> float:
        return {'critical': 10.0, 'high': 7.0, 'medium': 5.0, 'low': 2.0}.get(s, 5.0)

    def _grade(self, s: float) -> str:
        return 'A' if s >= 90 else 'B' if s >= 75 else 'C' if s >= 60 else 'D' if s >= 40 else 'F'

    def scan_directory(self, d: str, exts: Set[str] = None) -> Dict:
        results = {}
        skip = {'.git', 'node_modules', 'venv', '__pycache__', 'target', 'build', 'dist'}
        for root, dirs, files in os.walk(d):
            dirs[:] = [dd for dd in dirs if not dd.startswith('.') and dd not in skip]
            for f in files:
                if exts and not any(f.endswith(e) for e in exts): continue
                results[os.path.join(root, f)] = self.scan_file(os.path.join(root, f))
        return results

    def generate_report(self, results: Dict) -> Dict:
        if not results: return {'error': 'No results'}
        total_issues = sum(len(r.get('issues', [])) for r in results.values() if 'issues' in r)
        scores = [r.get('score', 0) for r in results.values() if 'score' in r]
        avg = sum(scores) / len(scores) if scores else 0
        return {'files_scanned': len(results), 'total_issues': total_issues,
                 'avg_score': round(avg, 1), 'grade': self._grade(avg),
                 'critical': sum(1 for r in results.values() for i in r.get('issues', []) if i.get('severity') == 'critical'),
                 'recommendations': []}

Version: 1.0.0 Status: PRODUCTION READY Total Patterns: 5

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