docs: add analysis and implementation reports for VoltAgent integration
- VoltAgent repository analysis and validation reports - Similar skills analysis and implementation tracking - HTML to markdown conversion report - Final skills count verification
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scripts/analyze_remaining_similar_skills.py
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scripts/analyze_remaining_similar_skills.py
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#!/usr/bin/env python3
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"""
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Analyze remaining similar skills to determine if they are truly new
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and worth adding to the repository.
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"""
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import json
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import re
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from pathlib import Path
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from typing import Dict, List, Tuple
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from urllib.parse import urlparse
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from urllib.request import urlopen, Request
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from urllib.error import URLError, HTTPError
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def normalize_skill_name(name: str) -> str:
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"""Normalize skill name to kebab-case."""
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# Remove special chars, convert to lowercase, replace spaces/hyphens
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name = re.sub(r'[^\w\s-]', '', name.lower())
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name = re.sub(r'[\s_]+', '-', name)
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name = re.sub(r'-+', '-', name)
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return name.strip('-')
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def check_url_accessible(url: str) -> bool:
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"""Check if URL is accessible."""
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try:
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req = Request(url, method='HEAD')
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with urlopen(req, timeout=10) as response:
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return response.status == 200
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except (URLError, HTTPError, Exception):
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return False
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def get_repo_base_url(github_url: str) -> str:
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"""Extract base GitHub repository URL."""
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# Handle various GitHub URL formats
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patterns = [
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r'https://github\.com/([^/]+/[^/]+)',
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r'github\.com/([^/]+/[^/]+)',
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]
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for pattern in patterns:
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match = re.search(pattern, github_url)
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if match:
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return f"https://github.com/{match.group(1)}"
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return None
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def check_skill_file_exists(repo_url: str, skill_path: str = None) -> Tuple[bool, str]:
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"""Check if SKILL.md exists in the repository."""
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base_url = get_repo_base_url(repo_url)
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if not base_url:
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return False, None
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# Common paths to check
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paths_to_check = [
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f"{base_url}/raw/main/{skill_path}/SKILL.md" if skill_path else f"{base_url}/raw/main/SKILL.md",
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f"{base_url}/raw/main/skills/{skill_path}/SKILL.md" if skill_path else None,
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f"{base_url}/raw/master/{skill_path}/SKILL.md" if skill_path else f"{base_url}/raw/master/SKILL.md",
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f"{base_url}/blob/main/{skill_path}/SKILL.md" if skill_path else f"{base_url}/blob/main/SKILL.md",
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]
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for path in paths_to_check:
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if path and check_url_accessible(path):
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return True, path
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return False, None
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def analyze_similarity(skill_name: str, similar_skills: List[str], existing_skills: Dict) -> Dict:
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"""Analyze how similar a skill is to existing ones."""
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analysis = {
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'is_duplicate': False,
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'is_complementary': False,
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'similarity_score': 0.0,
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'closest_match': None,
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'reasoning': []
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}
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skill_lower = skill_name.lower()
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# Check for exact or near-exact matches
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for existing_name, existing_data in existing_skills.items():
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existing_lower = existing_name.lower()
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# Exact match
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if skill_lower == existing_lower:
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analysis['is_duplicate'] = True
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analysis['closest_match'] = existing_name
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analysis['reasoning'].append(f"Exact match with existing skill: {existing_name}")
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return analysis
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# Check if one contains the other
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if skill_lower in existing_lower or existing_lower in skill_lower:
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if abs(len(skill_lower) - len(existing_lower)) <= 3:
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analysis['is_duplicate'] = True
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analysis['closest_match'] = existing_name
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analysis['similarity_score'] = 0.9
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analysis['reasoning'].append(f"Near-exact match: '{skill_name}' vs '{existing_name}'")
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return analysis
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# Check similarity with similar skills list
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for similar in similar_skills:
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if similar.lower() in existing_skills:
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existing_data = existing_skills[similar.lower()]
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# If the similar skill exists, this might be a duplicate
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analysis['similarity_score'] = 0.7
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analysis['closest_match'] = similar
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analysis['reasoning'].append(f"Similar to existing skill: {similar}")
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# Determine if complementary
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if analysis['similarity_score'] < 0.5:
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analysis['is_complementary'] = True
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analysis['reasoning'].append("Low similarity - likely complementary skill")
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return analysis
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def main():
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base_dir = Path(__file__).parent.parent
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# Load remaining similar skills
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remaining_file = base_dir / "remaining_similar_skills.json"
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if not remaining_file.exists():
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print("❌ remaining_similar_skills.json not found. Run the analysis first.")
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return
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with open(remaining_file, 'r') as f:
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data = json.load(f)
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# Load existing skills
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catalog_file = base_dir / "data" / "catalog.json"
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with open(catalog_file, 'r') as f:
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catalog = json.load(f)
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existing_skills = {s['name'].lower(): s for s in catalog.get('skills', [])}
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print(f"🔍 Analyzing {len(data['skills'])} remaining similar skills...\n")
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results = {
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'truly_new': [],
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'duplicates': [],
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'complementary': [],
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'needs_review': [],
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'invalid_sources': []
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}
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for skill in data['skills']:
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skill_name = skill['name']
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print(f"Analyzing: {skill_name}")
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# Skip if already exists
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if skill['exists_in_catalog'] or skill['folder_exists']:
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results['duplicates'].append({
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'name': skill_name,
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'reason': 'Already exists in repository',
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'url': skill['url']
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})
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continue
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# Check source accessibility
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exists, raw_url = check_skill_file_exists(skill['url'], skill.get('skill_part'))
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if not exists:
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results['invalid_sources'].append({
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'name': skill_name,
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'url': skill['url'],
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'reason': 'SKILL.md not found or URL inaccessible'
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})
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continue
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# Analyze similarity
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similarity_analysis = analyze_similarity(
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skill_name,
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skill['similar_to'],
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existing_skills
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)
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skill_result = {
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'name': skill_name,
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'url': skill['url'],
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'raw_url': raw_url,
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'description': skill['description'],
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'org': skill['org'],
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'category': skill['category'],
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'similar_to': skill['similar_to'],
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'similarity_analysis': similarity_analysis
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}
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if similarity_analysis['is_duplicate']:
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results['duplicates'].append(skill_result)
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elif similarity_analysis['is_complementary']:
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results['complementary'].append(skill_result)
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else:
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results['needs_review'].append(skill_result)
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# Generate report
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report = {
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'summary': {
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'total_analyzed': len(data['skills']),
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'truly_new': len(results['complementary']),
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'duplicates': len(results['duplicates']),
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'needs_review': len(results['needs_review']),
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'invalid_sources': len(results['invalid_sources'])
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},
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'results': results
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}
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output_file = base_dir / "similar_skills_analysis.json"
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with open(output_file, 'w') as f:
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json.dump(report, f, indent=2)
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print(f"\n✅ Analysis complete!")
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print(f"📊 Summary:")
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print(f" - Truly new (complementary): {len(results['complementary'])}")
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print(f" - Duplicates: {len(results['duplicates'])}")
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print(f" - Needs review: {len(results['needs_review'])}")
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print(f" - Invalid sources: {len(results['invalid_sources'])}")
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print(f"\n📄 Full report saved to: {output_file}")
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if __name__ == "__main__":
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main()
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