2d • General discussion
Build an AI keyword research tool + autoblogger
I Built a Blog Writer That Costs $0 to Run.
The secret? Content templates + intelligent mixing + local data.
💎 How the mixing works:
1. Store 1,000+ pre-written sections
2. Extract entities (service, location, problem)
3. Replace placeholders with extracted entities
4. Add transitions between sections
5. Reorder for SEO flow
Result: Unique content that reads like human wrote it.
Copy and paste the following technical prompt into openclaw gateway or your vibe coder of choice:
The app: SEO Blog Post Generator
What it does:
- Input: "10 tips for lawn care in Austin"
- Output: 1,500-word SEO article
The Custom AI Algorithm:
```python
def generate_blog_post(topic, location, word_count=1500):
# 1. Research phase (local data)
# 2. Outline generation (rule-based)
outline = [
f"Introduction: {topic} in {location}",
f"Section 1: {keywords[0]} - Why it matters",
f"Section 2: {keywords[1]} - Best practices",
f"Section 3: {keywords[2]} - Common mistakes",
f"FAQ Section: Answer {len(questions)} questions",
f"Conclusion: Call to action"
]
# 3. Content generation (template-based + mixing)
content = []
for section in outline:
# Mix relevant pre-written content
content.append(
mix_templates(
topic=topic,
location=location,
keywords=keywords,
section_type=detect_section(section)
)
)
# 4. SEO optimization
optimized = apply_seo(content, keywords, location)
return optimized
```
Next.js frontend → Supabase for templates → Custom algo for mixing
Share your repo when done 👇
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Build an AI keyword research tool + autoblogger
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