improve-prompt

Improve Prompt

Transform prompts into optimized, production-ready versions.

Purpose

Analyze and enhance prompts by:

• Identifying weaknesses and ambiguities
• Applying prompt engineering best practices
• Optimizing for specific models (Claude, Gemini, GPT)
• Structuring for consistent outputs
• Adding appropriate constraints and examples

When to Use

Ideal for:

• Prompts that get inconsistent results
• Prompts that need to work across models
• Complex prompts requiring structure
• Prompts for production use

Avoid when:

• Simple, one-off questions
• Conversational queries

Workflow

Step 1: Analyze Current Prompt

Evaluate the prompt for:

• Clarity: Is the task unambiguous?
• Completeness: Is all necessary context provided?
• Structure: Is it well-organized?
• Constraints: Are boundaries defined?
• Examples: Are examples provided if needed?
• Output format: Is expected output specified?

Step 2: Identify Improvements

Common issues to address:

• Vague instructions → Make specific
• Missing context → Add relevant background
• No output format → Specify structure
• No examples → Add few-shot examples
• No constraints → Add guardrails
• Too long → Consolidate and prioritize

Step 3: Apply Best Practices

For Claude:

• Use XML tags for structure
• Leverage extended thinking for complex tasks
• Request step-by-step reasoning
• Use positive framing ("do X" not "don't do Y")

For all models:

• Put important instructions at start and end
• Use numbered steps for sequences
• Provide concrete examples
• Specify output format explicitly
• Include edge case handling

Step 4: Generate Improved Prompt

Output the optimized prompt with:

• Clear structure
• Explicit instructions
• Defined output format
• Examples if beneficial

Output Format

## Prompt Analysis

**Original prompt issues:**
1. [Issue 1]
2. [Issue 2]

**Improvements applied:**
1. [Improvement 1]
2. [Improvement 2]

---

## Improved Prompt

[The optimized prompt, ready to copy]

---

## Usage Notes

- **Best for:** [model/use case]
- **Expected output:** [description]
- **Variations:** [any suggested variations]

Quality Gates

• All ambiguities resolved
• Output format specified
• Appropriate length (not bloated)
• Tested mentally for edge cases
• Model-appropriate techniques used

Examples

Example: Vague prompt improvement

Before: Summarize this document

After: Summarize the following document in 3-5 bullet points. Focus on:

Key findings or conclusions Important data points Recommended actions

Format each bullet as: [Topic]: [1-2 sentence summary] [Document content here]