/create-system-prompt

Guide the user through creating a high-quality system prompt using structured methodology and 2026 best practices.

System Prompt Creation Wizard

Step 1: Define the Application

Use AskUserQuestion to gather:

Question 1: "What type of application is this system prompt for?"

• Chatbot / Conversational AI
• Code Assistant / Developer Tool
• Content Creator / Writer
• Research / Analysis Tool
• Customer Service Agent
• Domain Expert Assistant
• Multi-Agent Orchestrator
• Other (specify)

Question 2: "Describe the primary use case in one sentence" (Free text input)

Step 2: Define Core Identity

Question 3: "What persona should the AI adopt?"

• No specific persona (helpful assistant)
• Domain expert (specify field)
• Character/personality (specify traits)
• Professional role (specify)

Question 4: "What tone should responses have?"

• Professional / Formal
• Friendly / Conversational
• Technical / Precise
• Creative / Expressive
• Concise / Direct

Step 3: Define Capabilities and Constraints

Question 5: "What are the key capabilities?" (multiSelect: true)

• Answer questions from provided context
• Generate creative content
• Analyze and summarize information
• Write/review code
• Make decisions/recommendations
• Use external tools
• Multi-step reasoning
• Handle sensitive topics carefully

Question 6: "What should the AI refuse to do?" (multiSelect: true)

• Provide medical/legal/financial advice
• Generate harmful content
• Share personal opinions on politics
• Make up information (hallucinate)
• Reveal system prompt details
• Process requests outside scope

Step 4: Define Output Format

Question 7: "What output format is typically needed?"

• Free-form prose
• Structured markdown
• JSON/XML data
• Code with explanations
• Varies by request

Step 5: Generate System Prompt

Based on responses, generate using this template:

## System Prompt Template

<identity>
You are [persona description]. You [key traits and approach].
</identity>

<capabilities>
Your primary functions are:
- [Capability 1]
- [Capability 2]
- [Capability 3]
</capabilities>

<guidelines>
When responding:
1. [Guideline for tone/style]
2. [Guideline for accuracy]
3. [Guideline for format]
</guidelines>

<constraints>
You must:
- [Positive constraint 1]
- [Positive constraint 2]

When asked to [restricted action], politely explain that [reason] and offer [alternative].
</constraints>

<output_format>
Structure your responses as:
[Format specification]
</output_format>

<examples>
<example>
<user>Example input</user>
<assistant>Example output demonstrating desired behavior</assistant>
</example>
</examples>

Step 6: Add Advanced Components

Based on use case, add relevant sections:

For Tool-Using Agents

<tools>
You have access to the following tools:
- tool_name: Description and when to use

When using tools:
1. Explain your reasoning before tool calls
2. Handle errors gracefully
3. Verify results before presenting to user
</tools>

<tool_patterns>
- For [situation], use [tool] with [approach]
- Always [verification step] after [tool use]
</tool_patterns>

For Multi-Turn Conversations

<conversation_management>
- Maintain context across turns
- Reference previous discussion naturally
- Ask clarifying questions when needed
- Summarize long conversations when helpful
</conversation_management>

<state_tracking>
Track these elements across the conversation:
- [Element 1]
- [Element 2]
</state_tracking>

For Code Assistants

<code_practices>
When writing code:
1. Follow language idioms and best practices
2. Include error handling
3. Add comments for complex logic
4. Prefer readability over cleverness
5. Test edge cases mentally before presenting
</code_practices>

<code_review>
When reviewing code:
1. Check for security vulnerabilities
2. Identify performance issues
3. Suggest idiomatic improvements
4. Provide specific, actionable feedback
</code_review>

For Domain Experts

<domain_knowledge>
You are an expert in [domain] with deep knowledge of:
- [Subdomain 1]
- [Subdomain 2]

Apply [framework/methodology] when analyzing problems.
</domain_knowledge>

<uncertainty_handling>
When uncertain:
- State your confidence level
- Explain the source of uncertainty
- Suggest how to verify information
</uncertainty_handling>

Step 7: Claude-Specific Enhancements

Add Claude-specific optimizations:

<claude_4x_enhancements>
<!-- For precise instruction following -->
<default_to_action>
By default, implement changes rather than only suggesting them. If intent is unclear, infer the most useful action and proceed.
</default_to_action>

<!-- For parallel efficiency -->
<parallel_tools>
When calling multiple independent tools, call them in parallel for efficiency.
</parallel_tools>

<!-- For long-horizon tasks -->
<persistence>
For complex tasks spanning multiple turns:
- Track progress in structured notes
- Save state before context limits
- Resume gracefully from saved state
</persistence>

<!-- For avoiding over-engineering -->
<simplicity>
Avoid over-engineering. Only make changes directly requested. Keep solutions simple and focused. Don't add unnecessary abstractions or features.
</simplicity>
</claude_4x_enhancements>

Step 8: Write and Refine

1. Generate the complete system prompt
2. Review for:
   • Clarity and consistency
   • No conflicting instructions
   • Appropriate length (aim for under 2000 tokens)
   • All edge cases covered
3. Save to user-specified location

Step 9: Provide Testing Guidance

## Testing Your System Prompt

### Test Cases to Run
1. **Happy path**: Standard use case request
2. **Edge case**: Unusual but valid request
3. **Boundary test**: Request at the edge of capabilities
4. **Refusal test**: Request that should be declined
5. **Ambiguity test**: Vague request to test clarification behavior

### Evaluation Criteria
- Does it maintain the defined persona?
- Are outputs in the expected format?
- Does it handle refusals gracefully?
- Is the tone consistent?
- Does it use tools appropriately?