zircote

Blog Post Generation Prompt - zircote Brand

Use this prompt template with Claude or other AI assistants to generate blog posts that match the zircote brand voice and style.

Template Variables

Fill in these values before using the prompt:

Generation Prompt

You are writing a technical blog post for zircote.com, the personal site of
Robert Allen, a technologist building AI-powered developer tools and
precision agriculture systems.

BRAND VOICE:
- Technical but accessible
- Direct and practical
- Code-first explanations
- Honest about tradeoffs
- From hands-on experience

TOPIC: 

TARGET AUDIENCE: 

KEY POINTS TO COVER:


REQUIREMENTS:

1. FRONTMATTER (Jekyll format):
   ---
   layout: post
   title: "[50-60 chars, include primary keyword]"
   date: YYYY-MM-DD
   categories: [category1, category2]
   tags: [tag1, tag2, tag3, tag4, tag5]
   excerpt: "[150-160 chars, compelling summary]"
   comments: true
   ---

2. STRUCTURE:
   - Hook: Start with a problem or insight (2-3 sentences)
   - Context: Why this matters to the reader
   - Main Content:  with code examples
   - Practical Application: Real-world usage
   - Conclusion: Key takeaways and next steps

3. CODE EXAMPLES:
   - Include working code snippets
   - Use proper syntax highlighting (```php, ```python, etc.)
   - Add inline comments explaining key lines
   - Show expected output where helpful

4. FORMATTING:
   - Use H2 (##) for main sections
   - Use H3 (###) for subsections
   - Use tables for comparisons
   - Use bullet points for lists
   - Keep paragraphs short (3-4 sentences max)

5. LINKS:
   - Link to relevant GitHub repositories
   - Link to official documentation
   - Link to related blog posts if applicable

6. SEO:
   - Primary keyword in title and first paragraph
   - Natural keyword usage (don't force it)
   - Descriptive alt text for any images
   - Internal links to other posts/projects

WORD COUNT TARGET:  words

CALL TO ACTION: 

Generate the complete blog post now.

Example Usage

TOPIC: Introducing the new git-adr search command
AUDIENCE: Software architects and developers using ADRs
KEY_POINTS:
  - Natural language search across ADR history
  - Semantic understanding vs keyword matching
  - Integration with Claude Code
  - Performance benchmarks
WORD_COUNT: 1500
CALL_TO_ACTION: Install git-adr and try the search command

Post-Generation Checklist