OPRO DSPy Prompt Optimizer AI Agent

What This Agent Does

This AI Prompt Optimization Agent is an intelligent workflow that automatically tests, evaluates, and improves your AI prompts to achieve better results. It takes your initial prompt and test input, generates a response, evaluates the quality of that response against your expected output, and then provides you with an optimized version of your prompt that's more likely to produce the results you want.

Key benefits include:

• Save hours of manual prompt iteration by automating the testing and refinement process
• Achieve better AI outputs through systematic evaluation and optimization
• Reduce trial-and-error with data-driven prompt improvements
• Document what works with clear before-and-after comparisons

This workflow is perfect for developing customer service responses, content generation templates, data extraction prompts, or any scenario where you need consistent, high-quality AI outputs.

Who Is It For

This agent is ideal for:

• AI/ML Engineers who need to optimize prompts for production applications and want systematic testing frameworks
• Content Creators who use AI assistance regularly and want to refine their prompts for better, more consistent outputs
• Product Managers building AI-powered features who need to validate prompt performance before deployment
• Customer Success Teams developing AI chatbot responses and want to ensure quality interactions
• Developers integrating Claude into applications who need to fine-tune prompts for specific use cases
• Anyone who finds themselves repeatedly tweaking prompts manually and wants an automated solution

Required Integrations

Anthropic (Claude AI)

Why it's needed: This workflow uses Claude AI three times - once to generate a response from your initial prompt, once to evaluate that response against your expectations, and once to create an optimized version of your prompt. Anthropic's Claude models power the entire optimization cycle.

Setup steps:

1. Create an Anthropic account by visiting console.anthropic.com
2. Navigate to API Keys in your account settings
3. Generate a new API key - give it a descriptive name like "TaskAGI Prompt Optimizer"
4. Copy the API key immediately (it won't be shown again)
5. Set up billing in your Anthropic account to ensure API access remains active

How to obtain API credentials:

• Go to your Anthropic Console
• Click on "API Keys" in the left sidebar
• Click "Create Key"
• Name your key and set appropriate permissions
• Copy the key that starts with sk-ant-

Configuration in TaskAGI:

1. Navigate to Settings > Integrations in TaskAGI
2. Find Anthropic in the integrations list
3. Click Connect or Add Integration
4. Paste your API key in the authentication field
5. Click Test Connection to verify it works
6. Save the integration

Important: This workflow uses the claude-sonnet-4-5-20250929 model, which provides an excellent balance of performance and cost-effectiveness for prompt optimization tasks.

Configuration Steps

Step 1: Configure the Form Trigger

The Form Trigger node is your entry point. This is where you'll input the data needed for prompt optimization:

• initial_prompt: Your current prompt that you want to optimize (the instructions you're giving to Claude)
• test_input: Sample input data to test your prompt against
• expected_output: What you expect the AI to produce (used for evaluation)

Example configuration:

initial_prompt: "Summarize the following customer feedback in 2 sentences."
test_input: "I love your product but the shipping took forever and the box was damaged."
expected_output: "Customer appreciates the product quality but experienced shipping delays and packaging damage."

Step 2: AI Response Generator Configuration

The AI Response Generator node takes your initial prompt and test input to create an actual response. This node is pre-configured with:

• Model: claude-sonnet-4-5-20250929 (optimal for most use cases)
• Prompt structure: Automatically combines your initial prompt with the test input
• Temperature: Set to balance creativity and consistency

What happens here: Claude receives your initial prompt and test input, then generates a response exactly as it would in production. This gives you real data to evaluate.

Step 3: AI Response Evaluator Configuration

The AI Response Evaluator analyzes the generated response against your expected output. It examines:

• Accuracy: Does the response match what you expected?
• Completeness: Are all required elements present?
• Quality: Is the response well-structured and appropriate?
• Gaps: What's missing or could be improved?

Data flow: This node receives the test input from the form trigger and the generated response from the previous node, creating a comprehensive evaluation report.

Step 4: AI Prompt Optimizer Configuration

The AI Prompt Optimizer is where the magic happens. This node acts as a world-class prompt engineer, analyzing:

• Your original prompt
• The generated response
• The evaluation results
• The gap between actual and expected output

Output: You'll receive an optimized prompt with:

• Specific improvements explained
• Reasoning for each change
• A complete, ready-to-use optimized prompt

Step 5: Format Results Configuration

The Format Results node structures all the data into an easy-to-read format. This node organizes:

• Original prompt and optimized prompt side-by-side
• Generated response and evaluation
• Clear recommendations for implementation

No configuration needed - this node automatically processes the data from previous steps.

Testing Your Agent

Running Your First Test

1. Click the "Run" button on the Form Trigger node
2. Fill in the form fields:
   • Enter your current prompt in initial_prompt
   • Provide realistic test data in test_input
   • Describe your desired outcome in expected_output
3. Submit the form to start the workflow

What to Verify at Each Step

After AI Response Generator:

• Check that a response was generated
• Verify it used your initial prompt correctly
• Confirm the test input was processed

After AI Response Evaluator:

• Review the evaluation score or assessment
• Read the identified strengths and weaknesses
• Note specific areas flagged for improvement

After AI Prompt Optimizer:

• Compare the original and optimized prompts
• Understand the reasoning behind changes
• Check that the optimization addresses evaluation findings

Expected Results and Success Indicators

✅ Successful execution shows:

• All nodes turn green/completed
• Formatted results appear with clear sections
• Optimized prompt includes specific improvements
• Evaluation explains the gap between actual and expected output

✅ Quality indicators:

• The optimized prompt is more specific than the original
• Recommendations are actionable and clear
• The evaluation identifies concrete improvement areas

Troubleshooting

Common Configuration Issues

Problem: "API key invalid" error

• Solution: Verify your Anthropic API key is correctly entered in TaskAGI integrations
• Check that the key starts with sk-ant-
• Ensure your Anthropic account has active billing

Problem: "Model not found" error

• Solution: Confirm you have access to Claude Sonnet 4 in your Anthropic account
• Check your API tier supports the specified model
• Try updating to the latest model version if deprecated

Problem: Workflow stops at AI Response Generator

• Solution: Check that your initial_prompt field isn't empty
• Verify the prompt doesn't contain formatting that breaks the API call
• Review Anthropic API status for any outages

Problem: Evaluation seems generic or unhelpful

• Solution: Provide more specific expected_output descriptions
• Include concrete examples of what good output looks like
• Make your test input representative of real use cases

Problem: Optimized prompt is too similar to original

• Solution: Your original prompt might already be well-optimized
• Try a more challenging test case that reveals weaknesses
• Provide more detailed expected output criteria

Error Message Explanations

• "Rate limit exceeded": You've made too many API calls. Wait a few minutes or upgrade your Anthropic plan.
• "Context length exceeded": Your prompt or input is too long. Break it into smaller chunks or summarize.
• "Invalid request format": Check for special characters or formatting issues in your form inputs.

Next Steps

After Successful Setup

1. Test with multiple scenarios - Run 3-5 different test cases to see how the optimizer handles various situations
2. Implement the optimized prompt - Copy the improved prompt into your production workflow
3. Measure the improvement - Compare outputs before and after optimization
4. Create a prompt library - Save your optimized prompts for reuse across projects

Optimization Suggestions

For better results:

• Use specific, measurable criteria in your expected output descriptions
• Test with edge cases that challenge your prompt
• Run multiple iterations - optimize the optimized prompt for even better results
• Document patterns you notice in successful optimizations

Advanced usage tips:

• Create a database of optimized prompts for different use cases
• Build a feedback loop by testing optimized prompts with real users
• Combine this workflow with A/B testing to validate improvements
• Schedule regular prompt reviews to catch degradation over time

Scaling Your Prompt Optimization

• Batch processing: Queue multiple prompts for optimization during off-hours
• Team collaboration: Share optimized prompts with your team through documentation
• Version control: Track prompt versions and their performance metrics
• Integration: Connect this workflow to your production systems for continuous improvement

Pro tip: Set up a monthly review where you run your most-used prompts through this optimizer to catch any drift or opportunities for improvement as AI models evolve.