Prompt Author

Prompt Author

Creates high-quality, reusable prompts for AI workflows. This is the core skill — everything else (layouts, exports) flows from prompts.

When to Use

Trigger phrases (exact match):

• "write the master prompt"
• "draft the homepage prompt"
• "make a revision prompt"
• "create a prompt"
• "write a prompt for"
• "compose a prompt"
• "author a prompt"
• "generate a prompt"

Also triggers if:

• User describes a task and says "what prompt would do this?"
• User needs a prompt rewritten or optimized
• User says "this prompt isn't working, fix it"

Not a trigger if:

• User provides a prompt and says "run this" (that's execution, not authoring)
• User asks for the output the prompt would produce (that's generation, not authoring)

Before Starting

Ask (or infer) these:

1. Deliverable type: Image prompt, text prompt, or workflow prompt?
2. Subject: What is the prompt about?
3. Audience: Who will use this prompt? (affects complexity and specificity)
4. Platform: Which AI will run this? (Claude, Midjourney, DALL-E, GPT-4, etc.)
   • This affects syntax and constraints
5. Format: Single prompt or template with variables?
6. Brand file: Is there a BRAND.md to reference? (if not, use defaults)

Default if not specified:

• Type: text prompt (most common)
• Platform: Claude (default for opencode)
• Format: single prompt (no variables)
• Brand: technical + direct

Prompt Types and Anatomy

Type 1: Image Generation Prompt

Anatomy:

[Subject] + [Style] + [Composition] + [Technical specs] + [Mood/Atmosphere]

Example:

A modern SaaS dashboard interface, clean minimal design, light mode,
showing data visualization with line charts and bar graphs,
8K resolution, soft shadows, Figma-style UI design,
professional corporate aesthetic, morning light, screenshot quality

Platform-specific syntax:

Type 2: Text Generation Prompt

Anatomy:

[Role/Identity] + [Context] + [Task] + [Constraints] + [Output format] + [Tone]

Template:

You are a {role} with expertise in {domain}.
{Context: what the user already knows, what situation they're in}
{Task: what they need you to produce}
{Constraints: what to avoid, what must be included}
{Output format: how to structure the response}
{Tone: how to sound}

Example (blog post intro):

You are a senior engineer writing for a technical blog.
The reader is a fellow engineer evaluating whether to adopt a new library.
Write the first 3 paragraphs of a blog post about {topic}.
Start with a concrete problem, not a generic introduction.
No corporate language. Use "we" for Lightrains perspective.
Include one specific example with real metrics.
End with a hook that makes the reader want the next section.

Type 3: Workflow Prompt (Chain of Tasks)

Anatomy:

[Goal] + [Steps] + [Inputs] + [Outputs] + [Error handling]

Example:

Create a workflow that:
1. Takes a topic as input
2. Generates 3 related subtopics
3. For each subtopic, writes one paragraph
4. Combines into a coherent article
5. Outputs in markdown with ## headings

Inputs: {topic}
Outputs: {markdown article}
On failure: retry step, log error, continue if unsolvable

Step-by-Step Process

Step 1: Identify Prompt Type

Match the request to one of the three types:

Step 2: Extract Key Information

Ask (or infer) these for every prompt:

Required:

• What is the output? (image, text, action)
• Who is the audience?
• What is the context/situation?
• What must the output include?
• What must the output exclude?

Nice to have:

• Brand rules (from BRAND.md)
• Platform constraints
• Example of ideal output
• Anti-example of what to avoid

Step 3: Draft the Prompt

Follow this structure (in order):

1. Role assignment (if applicable)

   • Who is the AI acting as?
   • What expertise does it have?

2. Context provision

   • What situation are we in?
   • What does the user already know?

3. Task statement

   • What needs to be produced?
   • Use action verbs: "write", "generate", "create", "analyze"

4. Constraints

   • What to avoid (negative constraints)
   • What must be included (positive constraints)
   • Any rules or guardrails

5. Output format

   • Structure: markdown, JSON, list, paragraph
   • Length: short, medium, long
   • Any required elements

6. Tone guidance

   • How should it sound?
   • Any voice rules from brand file

Write prompts as if giving instructions to a capable junior — specific but not condescending.

Step 4: Optimize for Platform

Claude-specific optimizations:

• Use XML tags for structure: <context>, <task>, <output>
• Break complex tasks into numbered steps
• Include "think step by step" for reasoning tasks
• Add output validation instructions

Midjourney-specific optimizations:

• Start with subject
• End with style descriptors
• Use artist names for style references
• Include aspect ratio

DALL-E specific optimizations:

• Natural language, conversational
• Can include more detail than other platforms
• Avoid negative prompts (not supported)

Step 5: Add Variables (if template)

For reusable prompts, add variables:

Variable syntax:

{variable_name}

Example:

Write a blog post intro about {topic}
for {audience}
in {tone} tone

Variable types:

Step 6: Test the Prompt

For text prompts: Run the prompt and evaluate:

• Does it produce what was requested?
• Are constraints respected?
• Is the format correct?
• Is the tone appropriate?

For image prompts: Visualize mentally or run through:

• Are style descriptors coherent?
• Is composition clear?
• Are technical specs reasonable?

For workflow prompts: Trace through each step:

• Are dependencies correct?
• Can any step fail silently?
• Is the final output what's expected?

Step 7: Iterate Based on Test

Common fixes:

Output Formats

Single Prompt File

Save as prompts/{name}.md:

# {Prompt Name}

**Type:** {image/text/workflow}
**Platform:** {platform}
**Author:** {your name or 'agent'}

---

{Prompt text here}

---

## Variables

| Variable | Type | Description | Default |
|----------|------|-------------|---------|
| `{var1}` | string | What this controls | - |

## Example Usage

{Example with variables filled in}

## Notes

{Any caveats, tips, or context}

Prompt Collection File

For multiple related prompts, use a collection:

# {Collection Name}

## Prompts

### {Prompt 1}
...content...

### {Prompt 2}
...content...

---

## Usage Guide

{How to use these prompts together}

Quality Rubric

Rate each prompt on these dimensions:

Minimum passing scores:

• Clarity: 4+
• Completeness: 4+
• All others: 3+

If any score is below minimum:

• Identify the specific problem
• Fix it
• Retest

Common Pitfalls and Fixes

Pitfall 1: Vague Role Assignment

Bad:

You are a writer.

Good:

You are a senior backend engineer with 10 years of experience in distributed systems.
You have debugged production incidents at scale and understand operational trade-offs.

Pitfall 2: Missing Output Format

Bad:

Write about microservices.

Good:

Write a 2-paragraph explanation of microservices architecture.
Format:
- Paragraph 1: What it is (1 sentence) + why it matters (2 sentences)
- Paragraph 2: Main benefit (1 sentence) + trade-off (2 sentences)

Pitfall 3: Conflicting Constraints

Bad:

Write something short but comprehensive.

Fix:

Write exactly 3 sentences that cover the 3 most important points.
Prioritize: clarity > completeness > length.

Pitfall 4: Platform Mismatch

Bad for Claude (too verbose):

As a language model with extensive training data, I would like you to please
provide a detailed response regarding the topic of...

Good for Claude:

Provide a detailed response about {topic}.
Include: key points, examples, and a conclusion.

Pitfall 5: Variables Too Broad

Bad:

Write about {subject}.

Good:

Write a 200-word introduction about {topic} for {audience}.
Focus on {angle}: practical benefits, not theory.

Before/After Examples

Example 1: Image Prompt

Before:

Dashboard design for a SaaS app.

After:

A modern SaaS analytics dashboard, dark mode, featuring:
- Line chart showing 30-day user growth (upward trend)
- Bar chart showing revenue by plan (3 bars)
- KPI cards with percentage changes (+12%, +8%, -3%)
- User avatar cluster showing recent signups

Style: Clean Figma interface, soft shadows, subtle gradients
Colors: Dark navy background (#0F172A), white text, accent blue (#3B82F6)
Layout: Left sidebar (collapsed), main content area with 2-column grid
Quality: 8K, photorealistic, screenshot aesthetic
Mood: Professional, data-driven, confident

Example 2: Text Prompt

Before:

Write a blog post intro.

After:

Write the opening 3 paragraphs of a technical blog post.

Role: Senior engineer writing for peers
Audience: Developers evaluating a new tool or approach
Opening: Start with a specific problem, not a generic observation
Structure:
  - Paragraph 1: The problem (concrete, not abstract)
  - Paragraph 2: Why common solutions fail (specific reasons)
  - Paragraph 3: What we're about to show (the hook)

Constraints:
  - No "In this article..."
  - No corporate language
  - One specific example with metrics if possible
  - End with a question or challenge to the reader

Format: Markdown, ~200 words total

Example 3: Workflow Prompt

Before:

Generate content for a landing page.

After:

Create a landing page copy workflow that:

1. INPUT: {product_name}, {target_audience}, {primary_benefit}

2. Generate headlines (5 options):
   - Pattern A: Problem-first
   - Pattern B: Benefit-first
   - Pattern C: Question-based
   - Pattern D: Bold claim
   - Pattern E: WRYDWTD (What Race You Want to Die Doing)

3. For each headline, generate:
   - Subheadline (1 sentence)
   - 3 bullet points (benefit-focused)
   - CTA text (action-oriented, max 5 words)

4. OUTPUT FORMAT:
   ## Headline A: {headline}
   Subheadline: {text}
   Bullets:
   - {bullet 1}
   - {bullet 2}
   - {bullet 3}
   CTA: {text}

5. ERROR HANDLING:
   - If input missing: ask for {product_name} at minimum
   - If output too long: trim bullets to 2
   - If tone off: regenerate with "more {adjective}" instruction

Done Checklist

Before declaring complete:

• Prompt type identified
• Key information extracted (output, audience, constraints)
• Prompt drafted following anatomy template
• Optimized for target platform
• Variables defined (if template)
• Tested or mentally traced
• Iterated based on test results
• Saved to correct location (prompts/{name}.md or skill file)
• Quality rubric scores all pass minimums
• Example usage provided
• Notes/caveats documented

Cross-Skill Orchestration

Called by:

• User directly
• repo-bootstrap — if skills need prompts written
• bento-layout-director — for prompt templates

Feeds into:

• bento-layout-director — image prompts become layout concepts
• packaging-and-export — prompts are packaged as deliverables
• repo-bootstrap — prompts can be part of skill definitions

Depends on:

• brand-system-builder — for tone guidance (if brand file exists)

Edge Cases