feat: Implement intelligent auto-categorization for skills
- Added `scripts/auto_categorize_skills.py` to analyze skill names and descriptions, auto-assigning categories based on keyword matching. - Updated category distribution to show counts and sort categories by skill count in the Home page dropdown. - Created documentation in `docs/CATEGORIZATION_IMPLEMENTATION.md` and `docs/SMART_AUTO_CATEGORIZATION.md` detailing the new categorization process and usage. - Introduced `scripts/fix_year_2025_to_2026.py` to update all skill dates from 2025 to 2026. - Enhanced user experience by moving "uncategorized" to the bottom of the category list and displaying skill counts in the dropdown.
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Zied
275
scripts/auto_categorize_skills.py
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275
scripts/auto_categorize_skills.py
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#!/usr/bin/env python3
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"""
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Auto-categorize skills based on their names and descriptions.
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Removes "uncategorized" by intelligently assigning categories.
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Usage:
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python auto_categorize_skills.py
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python auto_categorize_skills.py --dry-run (shows what would change)
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"""
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import os
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import re
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import json
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import sys
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import argparse
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# Ensure UTF-8 output for Windows compatibility
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if sys.platform == 'win32':
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import io
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sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
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sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8')
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# Category keywords mapping
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CATEGORY_KEYWORDS = {
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'web-development': [
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'react', 'vue', 'angular', 'svelte', 'nextjs', 'gatsby', 'remix',
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'html', 'css', 'javascript', 'typescript', 'frontend', 'web', 'tailwind',
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'bootstrap', 'sass', 'less', 'webpack', 'vite', 'rollup', 'parcel',
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'rest api', 'graphql', 'http', 'fetch', 'axios', 'cors',
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'responsive', 'seo', 'accessibility', 'a11y', 'pwa', 'progressive',
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'dom', 'jsx', 'tsx', 'component', 'router', 'routing'
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],
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'backend': [
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'nodejs', 'node.js', 'express', 'fastapi', 'django', 'flask',
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'spring', 'java', 'python', 'golang', 'rust', 'c#', 'csharp',
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'dotnet', '.net', 'laravel', 'php', 'ruby', 'rails',
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'server', 'backend', 'api', 'rest', 'graphql', 'database',
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'sql', 'mongodb', 'postgres', 'mysql', 'redis', 'cache',
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'authentication', 'auth', 'jwt', 'oauth', 'session',
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'middleware', 'routing', 'controller', 'model'
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],
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'database': [
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'database', 'sql', 'postgres', 'postgresql', 'mysql', 'mariadb',
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'mongodb', 'nosql', 'firestore', 'dynamodb', 'cassandra',
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'elasticsearch', 'redis', 'memcached', 'graphql', 'prisma',
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'orm', 'query', 'migration', 'schema', 'index'
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],
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'ai-ml': [
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'ai', 'artificial intelligence', 'machine learning', 'ml',
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'deep learning', 'neural', 'tensorflow', 'pytorch', 'scikit',
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'nlp', 'computer vision', 'cv', 'llm', 'gpt', 'bert',
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'classification', 'regression', 'clustering', 'transformer',
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'embedding', 'vector', 'embedding', 'training', 'model'
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],
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'devops': [
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'devops', 'docker', 'kubernetes', 'k8s', 'ci/cd', 'git',
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'github', 'gitlab', 'jenkins', 'gitlab-ci', 'github actions',
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'aws', 'azure', 'gcp', 'terraform', 'ansible', 'vagrant',
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'deploy', 'deployment', 'container', 'orchestration',
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'monitoring', 'logging', 'prometheus', 'grafana'
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],
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'cloud': [
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'aws', 'amazon', 'azure', 'gcp', 'google cloud', 'cloud',
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'ec2', 's3', 'lambda', 'cloudformation', 'terraform',
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'serverless', 'functions', 'storage', 'cdn', 'distributed'
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],
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'security': [
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'security', 'encryption', 'cryptography', 'ssl', 'tls',
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'hashing', 'bcrypt', 'jwt', 'oauth', 'authentication',
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'authorization', 'firewall', 'penetration', 'audit',
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'vulnerability', 'privacy', 'gdpr', 'compliance'
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],
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'testing': [
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'test', 'testing', 'jest', 'mocha', 'jasmine', 'pytest',
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'unittest', 'cypress', 'selenium', 'puppeteer', 'e2e',
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'unit test', 'integration', 'coverage', 'ci/cd'
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],
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'mobile': [
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'mobile', 'android', 'ios', 'react native', 'flutter',
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'swift', 'kotlin', 'objective-c', 'app', 'native',
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'cross-platform', 'expo', 'cordova', 'xamarin'
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],
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'game-development': [
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'game', 'unity', 'unreal', 'godot', 'canvas', 'webgl',
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'threejs', 'babylon', 'phaser', 'sprite', 'physics',
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'collision', '2d', '3d', 'shader', 'rendering'
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],
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'data-science': [
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'data', 'analytics', 'science', 'pandas', 'numpy', 'scipy',
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'jupyter', 'notebook', 'visualization', 'matplotlib', 'plotly',
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'statistics', 'correlation', 'regression', 'clustering'
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],
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'automation': [
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'automation', 'scripting', 'selenium', 'puppeteer', 'robot',
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'workflow', 'automation', 'scheduled', 'trigger', 'integration'
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],
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'content': [
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'markdown', 'documentation', 'content', 'blog', 'writing',
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'seo', 'meta', 'schema', 'og', 'twitter', 'description'
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]
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}
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def categorize_skill(skill_name, description):
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"""
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Intelligently categorize a skill based on name and description.
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Returns the best matching category or None if no match.
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"""
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combined_text = f"{skill_name} {description}".lower()
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# Score each category based on keyword matches
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scores = {}
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for category, keywords in CATEGORY_KEYWORDS.items():
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score = 0
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for keyword in keywords:
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# Prefer exact phrase matches with word boundaries
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if re.search(r'\b' + re.escape(keyword) + r'\b', combined_text):
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score += 2
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elif keyword in combined_text:
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score += 1
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if score > 0:
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scores[category] = score
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# Return the category with highest score
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if scores:
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best_category = max(scores, key=scores.get)
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return best_category
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return None
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def auto_categorize(skills_dir, dry_run=False):
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"""Auto-categorize skills and update generate_index.py"""
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skills = []
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categorized_count = 0
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already_categorized = 0
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failed_count = 0
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for root, dirs, files in os.walk(skills_dir):
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dirs[:] = [d for d in dirs if not d.startswith('.')]
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if "SKILL.md" in files:
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skill_path = os.path.join(root, "SKILL.md")
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skill_id = os.path.basename(root)
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try:
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with open(skill_path, 'r', encoding='utf-8') as f:
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content = f.read()
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# Extract name and description from frontmatter
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fm_match = re.search(r'^---\s*\n(.*?)\n---', content, re.DOTALL)
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if not fm_match:
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continue
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fm_text = fm_match.group(1)
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metadata = {}
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for line in fm_text.split('\n'):
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if ':' in line and not line.strip().startswith('#'):
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key, val = line.split(':', 1)
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metadata[key.strip()] = val.strip().strip('"').strip("'")
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skill_name = metadata.get('name', skill_id)
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description = metadata.get('description', '')
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current_category = metadata.get('category', 'uncategorized')
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# Skip if already has a meaningful category
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if current_category and current_category != 'uncategorized':
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already_categorized += 1
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skills.append({
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'id': skill_id,
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'name': skill_name,
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'current': current_category,
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'action': 'SKIP'
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})
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continue
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# Try to auto-categorize
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new_category = categorize_skill(skill_name, description)
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if new_category:
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skills.append({
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'id': skill_id,
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'name': skill_name,
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'current': current_category,
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'new': new_category,
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'action': 'UPDATE'
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})
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if not dry_run:
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# Update the SKILL.md file - add or replace category
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fm_start = content.find('---')
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fm_end = content.find('---', fm_start + 3)
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if fm_start >= 0 and fm_end > fm_start:
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frontmatter = content[fm_start:fm_end+3]
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body = content[fm_end+3:]
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# Check if category exists in frontmatter
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if 'category:' in frontmatter:
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# Replace existing category
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new_frontmatter = re.sub(
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r'category:\s*\w+',
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f'category: {new_category}',
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frontmatter
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)
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else:
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# Add category before the closing ---
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new_frontmatter = frontmatter.replace(
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'\n---',
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f'\ncategory: {new_category}\n---'
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)
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new_content = new_frontmatter + body
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with open(skill_path, 'w', encoding='utf-8') as f:
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f.write(new_content)
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categorized_count += 1
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else:
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skills.append({
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'id': skill_id,
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'name': skill_name,
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'current': current_category,
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'action': 'FAILED'
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})
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failed_count += 1
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except Exception as e:
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print(f"❌ Error processing {skill_id}: {str(e)}")
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# Print report
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print("\n" + "="*70)
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print("AUTO-CATEGORIZATION REPORT")
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print("="*70)
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print(f"\n📊 Summary:")
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print(f" ✅ Categorized: {categorized_count}")
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print(f" ⏭️ Already categorized: {already_categorized}")
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print(f" ❌ Failed to categorize: {failed_count}")
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print(f" 📈 Total processed: {len(skills)}")
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if categorized_count > 0:
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print(f"\n📋 Sample changes:")
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for skill in skills[:10]:
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if skill['action'] == 'UPDATE':
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print(f" • {skill['id']}")
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print(f" {skill['current']} → {skill['new']}")
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if dry_run:
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print(f"\n🔍 DRY RUN MODE - No changes made")
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else:
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print(f"\n💾 Changes saved to SKILL.md files")
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return categorized_count
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def main():
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parser = argparse.ArgumentParser(
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description="Auto-categorize skills based on content",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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python auto_categorize_skills.py --dry-run
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python auto_categorize_skills.py
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"""
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)
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parser.add_argument('--dry-run', action='store_true',
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help='Show what would be changed without making changes')
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args = parser.parse_args()
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base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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skills_path = os.path.join(base_dir, "skills")
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auto_categorize(skills_path, dry_run=args.dry_run)
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if __name__ == "__main__":
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main()
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53
scripts/fix_year_2025_to_2026.py
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53
scripts/fix_year_2025_to_2026.py
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@@ -0,0 +1,53 @@
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#!/usr/bin/env python3
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"""
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Update all skill dates from 2025 to 2026.
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Fixes the year mismatch issue.
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"""
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import os
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import re
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import sys
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# Ensure UTF-8 output for Windows compatibility
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if sys.platform == 'win32':
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import io
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sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
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sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8')
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def update_dates(skills_dir):
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"""Update all dates from 2025 to 2026"""
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updated_count = 0
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for root, dirs, files in os.walk(skills_dir):
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dirs[:] = [d for d in dirs if not d.startswith('.')]
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if "SKILL.md" in files:
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skill_path = os.path.join(root, "SKILL.md")
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skill_id = os.path.basename(root)
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try:
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with open(skill_path, 'r', encoding='utf-8') as f:
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content = f.read()
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# Replace 2025 with 2026 in date_added field
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if 'date_added: "2025-' in content:
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new_content = content.replace('date_added: "2025-', 'date_added: "2026-')
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with open(skill_path, 'w', encoding='utf-8') as f:
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f.write(new_content)
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print(f"OK {skill_id}")
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updated_count += 1
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except Exception as e:
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print(f"Error updating {skill_id}: {str(e)}")
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print(f"\nUpdated {updated_count} skills to 2026")
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return updated_count
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if __name__ == "__main__":
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base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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skills_path = os.path.join(base_dir, "skills")
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print("Updating all dates from 2025 to 2026...\n")
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update_dates(skills_path)
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print("\nDone! Run: python scripts/generate_index.py")
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@@ -62,7 +62,7 @@ def generate_index(skills_dir, output_file):
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skill_info = {
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"id": dir_name,
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"path": os.path.relpath(root, os.path.dirname(skills_dir)),
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"category": parent_dir if parent_dir != "skills" else "uncategorized",
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"category": parent_dir if parent_dir != "skills" else None, # Will be overridden by frontmatter if present
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"name": dir_name.replace("-", " ").title(),
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"description": "",
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"risk": "unknown",
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@@ -80,13 +80,19 @@ def generate_index(skills_dir, output_file):
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# Parse Metadata
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metadata = parse_frontmatter(content)
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# Merge Metadata
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# Merge Metadata (frontmatter takes priority)
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if "name" in metadata: skill_info["name"] = metadata["name"]
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if "description" in metadata: skill_info["description"] = metadata["description"]
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if "risk" in metadata: skill_info["risk"] = metadata["risk"]
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if "source" in metadata: skill_info["source"] = metadata["source"]
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if "date_added" in metadata: skill_info["date_added"] = metadata["date_added"]
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# Category: prefer frontmatter, then folder structure, then default
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if "category" in metadata:
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skill_info["category"] = metadata["category"]
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elif skill_info["category"] is None:
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skill_info["category"] = "uncategorized"
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# Fallback for description if missing in frontmatter (legacy support)
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if not skill_info["description"]:
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body = content
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Reference in New Issue
Block a user