tomevault-io System Prompt Engineering Skill
Design effective system prompts for custom agents that establish identity, rules, and behavior.
Purpose
Create system prompts that shape agent behavior across all conversations. System prompts are orders of magnitude more important than user prompts.
When to Use
- Creating new custom agents
- Establishing agent expertise
- Defining persistent rules
- Building specialized assistants
System Prompt vs User Prompt
| Aspect | System Prompt | User Prompt |
|---|---|---|
| Scope | All conversations | Single task |
| Persistence | Affects everything | Per-request |
| Impact | Orders of magnitude higher | Lower blast radius |
| Sections | Purpose, Instructions, Examples | All sections |
Key Sections
Purpose (Required)
Define who the agent is and what it does.
## Purpose
You are a security expert specializing in code review.
Your role is to identify vulnerabilities and suggest fixes.
You focus on OWASP Top 10 and secure coding practices.
Guidelines:
- Direct, clear identity statement
- Specific expertise area
- What the agent DOES
Instructions (Recommended)
Establish rules, constraints, and boundaries.
## Instructions
- Focus only on security concerns
- Always explain the reasoning behind findings
- Prioritize issues by severity (Critical, High, Medium, Low)
- Do not modify code without explicit permission
- When uncertain, ask clarifying questions
Guidelines:
- Bullet points for clarity
- Positive and negative rules
- Edge case handling
- Boundary definition
Examples (Critical)
Shape behavior through concrete examples.
## Examples
### Example 1: SQL Injection Finding
**Input:** "Review this login function"
**Output:** "Found SQL injection vulnerability at line 42. The user input is directly concatenated into the query string. Recommendation: Use parameterized queries instead."
### Example 2: Out of Scope Request
**Input:** "Fix this CSS styling issue"
**Output:** "That's outside my security focus. I specialize in security vulnerabilities, not styling. Consider consulting a frontend expert for CSS issues."
### Example 3: Clean Code
**Input:** "Check this authentication module"
**Output:** "Reviewed the authentication module. No security vulnerabilities found. The code follows secure practices: uses parameterized queries, hashes passwords with bcrypt, and implements rate limiting."
Guidelines:
- 2-4 diverse examples
- Cover common cases
- Include edge cases
- Show desired output format
Design Process
Step 1: Define Agent Identity
Answer:
- What expertise does this agent have?
- What domain does it operate in?
- What is its primary purpose?
- What tone should it use?
Step 2: Establish Boundaries
Answer:
- What should the agent do?
- What should the agent NOT do?
- When should it ask for clarification?
- What are its limitations?
Step 3: Create Examples
For each key scenario:
- What's a typical input?
- What's the ideal output?
- How should edge cases be handled?
Step 4: Validate Design
Check:
- Purpose is clear and specific
- Instructions are unambiguous
- Examples cover key scenarios
- Boundaries are well-defined
- Tone is consistent
What to Avoid
| Avoid | Why | Instead |
|---|---|---|
| Detailed workflows | Reduces autonomy | High-level guidelines |
| Dynamic variables | System prompt is static | Use user prompts |
| Prescriptive formats | Over-constrains | Flexible guidelines |
| Everything "just in case" | Context bloat | Only essentials |
System Prompt Architecture
---
name: agent-name
description: When to use this agent (for auto-delegation)
tools: [minimal tool set]
model: sonnet
color: blue
---
# Agent Name
## Purpose
[Identity and role definition]
## Instructions
[Rules and constraints]
## Examples
### Example 1: [Scenario]
**Input:** [typical input]
**Output:** [ideal output]
### Example 2: [Edge Case]
**Input:** [edge case input]
**Output:** [handling output]
### Example 3: [Boundary]
**Input:** [out-of-scope request]
**Output:** [how to decline/redirect]
Output Format
When designing a system prompt:
## System Prompt Design
**Agent Name:** [name]
**Domain:** [expertise area]
**Model:** [sonnet/opus/haiku]
### Purpose
[2-3 sentences defining identity]
### Instructions
- [rule 1]
- [rule 2]
- [rule 3]
### Examples
**Example 1:** [scenario]
- Input: [input]
- Output: [output]
**Example 2:** [scenario]
- Input: [input]
- Output: [output]
### Validation
- [ ] Purpose is specific
- [ ] Instructions are actionable
- [ ] Examples are diverse
- [ ] Boundaries are clear
Common Agent Types
Expert Agent
Focus: Deep domain knowledge
## Purpose
You are an expert in [domain] with deep knowledge of [specifics].
Guard Agent
Focus: Validation and safety
## Instructions
- Validate all inputs against [criteria]
- Block requests that [conditions]
- Log suspicious activity
Translator Agent
Focus: Format conversion
## Examples
### Input Format
[format A]
### Output Format
[format B]
Key Quote
"System prompts are orders of magnitude more important than user prompts. They run once and affect everything."
Cross-References
- @system-vs-user-prompts.md - Distinction and best practices
- @agent-expert-creation skill - Creating expert agents
- @one-agent-one-purpose.md - Specialization principle
Version History
- v1.0.0 (2025-12-26): Initial release
Last Updated
Date: 2025-12-26 Model: claude-opus-4-5-20251101
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