mirror of
https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering.git
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muratcankoylan
ace9c0aeb3
- Personal operating system for founders/creators as Claude Code skill - 6 isolated modules following context engineering principles - 4 automation scripts with tool-design consolidation - Complete skills traceability documentation
133 lines
4.2 KiB
Python
133 lines
4.2 KiB
Python
#!/usr/bin/env python3
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"""
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Content Ideas Generator
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Generates content ideas based on knowledge base and past successful content.
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"""
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import json
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import argparse
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from datetime import datetime
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from pathlib import Path
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BRAIN_ROOT = Path(__file__).parent.parent.parent
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def load_jsonl(filepath):
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"""Load JSONL file, skipping schema lines."""
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items = []
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if not filepath.exists():
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return items
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with open(filepath, 'r') as f:
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for line in f:
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line = line.strip()
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if not line:
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continue
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try:
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data = json.loads(line)
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if '_schema' not in data:
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items.append(data)
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except json.JSONDecodeError:
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continue
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return items
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def get_top_performing_content():
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"""Get posts with highest engagement."""
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posts = load_jsonl(BRAIN_ROOT / 'content' / 'posts.jsonl')
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# Sort by engagement metrics if available
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def engagement_score(post):
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metrics = post.get('metrics', {})
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return (
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metrics.get('likes', 0) +
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metrics.get('comments', 0) * 2 +
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metrics.get('reposts', 0) * 3
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)
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sorted_posts = sorted(posts, key=engagement_score, reverse=True)
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return sorted_posts[:5]
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def get_recent_bookmarks(category=None):
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"""Get recent bookmarks, optionally filtered by category."""
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bookmarks = load_jsonl(BRAIN_ROOT / 'knowledge' / 'bookmarks.jsonl')
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if category:
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bookmarks = [b for b in bookmarks if b.get('category') == category]
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# Sort by date, most recent first
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bookmarks.sort(key=lambda x: x.get('saved_at', ''), reverse=True)
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return bookmarks[:10]
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def get_undeveloped_ideas():
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"""Get ideas that haven't been developed yet."""
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ideas = load_jsonl(BRAIN_ROOT / 'content' / 'ideas.jsonl')
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raw_ideas = [i for i in ideas if i.get('status') == 'raw']
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return raw_ideas
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def generate_suggestions(pillar=None, count=5):
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"""Generate content suggestions."""
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output = f"""
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# Content Ideas Generator
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Generated: {datetime.now().isoformat()}
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Filter: {pillar or 'All pillars'}
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## Based on Top Performing Content
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"""
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top_posts = get_top_performing_content()
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if top_posts:
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output += "\nYour best performing content themes:\n"
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for post in top_posts[:3]:
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output += f"- {post.get('pillar', 'Unknown')}: {post.get('type', 'post')}\n"
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output += "\n**Suggestion**: Create more content in these high-performing areas.\n"
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else:
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output += "\nNo post history yet. Start creating!\n"
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output += """
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## From Your Knowledge Base
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"""
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bookmarks = get_recent_bookmarks(pillar)
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if bookmarks:
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output += "\nRecent topics you've been researching:\n"
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for bm in bookmarks[:5]:
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output += f"- {bm.get('title', 'Untitled')} ({bm.get('category', 'uncategorized')})\n"
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if bm.get('key_insights'):
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output += f" Key insight: {bm['key_insights'][0]}\n"
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output += "\n**Suggestion**: Turn these research topics into educational content.\n"
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else:
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output += "\nNo bookmarks yet. Save interesting content to fuel ideas.\n"
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output += """
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## Undeveloped Ideas
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"""
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ideas = get_undeveloped_ideas()
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if ideas:
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output += f"\nYou have {len(ideas)} undeveloped ideas:\n"
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for idea in ideas[:count]:
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output += f"- [{idea.get('priority', 'medium')}] {idea.get('idea', 'No content')}\n"
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output += "\n**Suggestion**: Pick one high-priority idea and develop it today.\n"
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else:
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output += "\nNo undeveloped ideas in the queue.\n"
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output += """
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## Quick Prompts
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1. "What's one thing I learned this week that others would find valuable?"
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2. "What's a common mistake I see in my industry?"
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3. "What question do I get asked most often?"
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4. "What worked for me that's counterintuitive?"
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5. "What do I wish I knew when I started?"
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"""
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return output
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Generate content ideas')
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parser.add_argument('--pillar', '-p', help='Filter by content pillar')
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parser.add_argument('--count', '-c', type=int, default=5, help='Number of ideas to show')
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args = parser.parse_args()
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print(generate_suggestions(args.pillar, args.count))
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