Creation Basics
Prompt Engineering Tips
Advanced techniques for crafting effective agent descriptions
Mastering agent prompts
The quality of your prompts directly impacts your agents’ performance. Small wording changes can significantly alter agent behavior.Your prompt is the foundation of your agent’s capabilities. Precision matters.
Essential prompt components
- Clear role definition
- Specific knowledge domains
- Defined personality traits
- Explicit capabilities
- Task descriptions
- Interaction guidelines
- Performance criteria
Effective structure
Advanced techniques
Role framing
Role framing
Frame your agent’s role as a professional position or expert identity.Less effective: “An agent that helps with marketing”More effective: “A senior digital marketing strategist with 15+ years of experience in B2B SaaS companies”
Contextual anchoring
Contextual anchoring
Provide specific contexts to guide your agent’s understanding of its purpose.Less effective: “An agent that helps with writing”More effective: “A writing coach for graduate students working on dissertations in the humanities”
Capability hierarchies
Capability hierarchies
Organize capabilities from fundamental to advanced, helping the agent prioritize.Example:
“The agent should have these capabilities, in order of priority:
- Identify investment opportunities based on financial metrics
- Analyze risk factors for each opportunity
- Create portfolio allocation recommendations
- Generate detailed investment reports”
Constraint definition
Constraint definition
Explicitly define boundaries for your agent’s behavior.Example:
“The agent must never:
- Make specific stock price predictions
- Recommend individual securities without disclaimers
- Present itself as a licensed financial advisor
- Guarantee returns on investments”
Reasoning patterns
Reasoning patterns
Define how your agent should approach problems.Analytical: “Break problems into components, examine each systematically, synthesize findings”Creative: “Explore broadly, make unexpected connections, evaluate and refine promising options”
Output formatting
Output formatting
Specify how information should be presented.Example:
“Structure information as:
- Executive summary (2-3 sentences)
- Key findings (bullet points)
- Detailed analysis (by topic)
- Recommendations (prioritized)
- Next steps (actionable items)“
Domain-specific patterns
Analytical agents
Focus on: Data handling, analytical frameworks, statistical approaches, visualization preferencesPattern: “Analyze [data] using [methods] to identify [insights], presenting results with [visualization] and indicating confidence levels.”
Creative agents
Focus on: Stylistic preferences, creative constraints, inspiration sources, iteration approachesPattern: “Generate [output] in the style of [reference], balancing [quality A] and [quality B], with variations exploring different [dimensions].”
Educational agents
Focus on: Teaching methodologies, knowledge scaffolding, assessment approaches, explanation techniquesPattern: “Teach [subject] from [level], using [methodology], adapting explanations based on comprehension.”
Operational agents
Focus on: Process definitions, decision criteria, exception handling, verification stepsPattern: “Manage [process] following [procedure], making decisions based on [criteria], handling exceptions by [approach].”
Example prompts
Financial advisor agent
Financial advisor agent
Content marketing strategist
Content marketing strategist
Iterative refinement process
1
Start with a basic prompt
Create your initial agent with a solid description.
2
Test thoroughly
Interact with your agent across various relevant scenarios.
3
Identify gaps
Note areas where your agent underperforms or misunderstands.
4
Refine your prompt
Revise your description to address specific issues.
5
Repeat
Continue this cycle until your agent performs consistently.
Keep records of your prompt revisions and how each change affected performance.
Troubleshooting common issues
Agent misunderstands purpose
Agent misunderstands purpose
- Performs tasks outside intended domain
- Fails to prioritize core functions
- Seems confused about its role
Agent lacks depth
Agent lacks depth
- Provides surface-level information
- Cannot handle specialized queries
- Indicates knowledge limitations
Inconsistent personality
Inconsistent personality
- Tone varies unpredictably
- Sometimes contradicts established character
- Personality doesn’t align with purpose
Struggles with complexity
Struggles with complexity
- Performs well on simple tasks but fails on complex ones
- Doesn’t break down problems effectively
- Provides incomplete solutions
Expert tips
- Use concrete examples of expected outputs to provide clear guidance.
- Define interaction patterns for different request types to create consistency.
- Anticipate edge cases with instructions for handling unusual or ambiguous inputs.
Prompt engineering is an evolving discipline. What works for one agent may not work for another. Stay experimental in your approach.