Prompt Optimizer
This skill optimizes system prompts for Claude Code agents by applying proven prompt engineering patterns from production systems.
When to Use This Skill
Use this skill when:
- •User provides a prompt and requests optimization
- •User asks for prompt improvement or refinement
- •User wants to apply best practices to agent instructions
- •User needs help with tool-use prompts or workflow automation
Process Overview
This skill uses a two-phase optimization approach:
Phase 1: Section-by-Section Analysis
- •Decompose the prompt into logical sections
- •Analyze each section independently
- •Apply relevant patterns with explicit attribution
- •Present findings per section
Phase 2: Full-Pass Integration
- •Review the complete optimized prompt holistically
- •Ensure cross-section coherence
- •Eliminate redundancies
- •Verify global consistency
Required Resources
Before beginning optimization, ALWAYS read:
references/prompt-engineering.md
This file contains the complete catalog of prompt engineering patterns that MUST be applied during optimization.
Phase 1: Section-by-Section Optimization
Step 1: Decompose the Prompt
Break the prompt into logical sections. Common sections include:
- •Role Definition: Who/what the agent is
- •Core Capabilities: What the agent can do
- •Tool Instructions: How to use specific tools
- •Constraints: What the agent must not do
- •Output Format: How to structure responses
- •Safety Instructions: Security and safety guidelines
- •Workflow Automation: Multi-step procedures
- •Examples: Demonstrations of correct behavior
- •Error Handling: How to handle failures
Not all prompts will have all sections. Identify what exists in the provided prompt.
Step 2: Analyze Each Section
For each section identified:
- •State the section name and current content
- •Identify applicable patterns from prompt-engineering.md
- •For EACH proposed change:
- •Pattern name (e.g., "Progressive Disclosure")
- •Why this pattern applies here
- •Expected behavioral impact
- •Show the specific change (before/after)
CRITICAL: Every change must have explicit pattern attribution. Changes without attribution are incomplete.
Step 3: Present Section Analysis
Present findings in this format:
## Section: [Section Name] ### Current Content [Original text] ### Applied Patterns #### Change 1 **Pattern**: [Pattern Name from prompt-engineering.md] **Rationale**: [Why this pattern applies] **Impact**: [Expected behavioral change] **Change**: Before: [original text] After: [optimized text] #### Change 2 [Same structure...]
Step 4: Handle Pattern Conflicts
When multiple patterns could apply to the same text, present options:
### Pattern Conflict Detected **Context**: [Section and text in question] **Option A**: [Pattern Name] - Application: [How it would be applied] - Benefits: [What it achieves] - Trade-offs: [What you might lose] **Option B**: [Pattern Name] - Application: [How it would be applied] - Benefits: [What it achieves] - Trade-offs: [What you might lose] **Recommendation**: [Which option and why]
Ask the user which approach they prefer before proceeding.
Phase 2: Full-Pass Integration
After completing section-by-section optimization and receiving user approval:
Step 1: Assemble the Optimized Prompt
Combine all optimized sections into a complete prompt.
Step 2: Global Analysis
Review the complete prompt for:
- •Cross-section coherence: Do sections work together harmoniously?
- •Redundancy elimination: Are any instructions repeated unnecessarily?
- •Consistency: Do all sections use consistent terminology and style?
- •Flow: Does the prompt follow a logical progression?
- •Completeness: Are there gaps between sections?
Step 3: Apply Global Patterns
Identify and apply patterns that only become apparent at the full-prompt level:
- •Emphasis Hierarchy: Are the most critical instructions properly emphasized?
- •Progressive Disclosure: Does complexity increase appropriately?
- •Rule Hierarchies: Are there conflicting priorities that need ordering?
- •Default Behaviors: Are failure modes and edge cases handled?
Step 4: Present Final Optimization
Present the complete optimized prompt with:
## Final Optimized Prompt [Complete optimized prompt] ## Global Changes Applied ### Change 1 **Pattern**: [Pattern Name] **Rationale**: [Why this global pattern was needed] **Impact**: [Expected improvement] **Sections Affected**: [Which sections were modified] [Additional global changes...] ## Summary **Total Changes**: [Number] **Patterns Applied**: [List of unique patterns used] **Key Improvements**: [3-5 bullet points of major improvements]
Quality Checklist
Before presenting the final optimized prompt, verify:
- • Every change has explicit pattern attribution
- • No section contradicts another section
- • Critical instructions use appropriate emphasis (CAPITAL, NEVER/ALWAYS, etc.)
- • Examples are provided where complexity is high
- • Anti-patterns are explicitly called out where relevant
- • Safety-critical operations have verbose instructions
- • Output format requirements are unambiguous
- • Tool usage hierarchies are clear
- • Default behaviors are specified for edge cases
- • The prompt follows progressive disclosure principles
Best Practices
Token Efficiency
- •Remove redundant explanations
- •Use concise examples over verbose descriptions
- •Consolidate related instructions
Behavioral Clarity
- •Use imperative voice ("Use X" not "You should use X")
- •State absolutes clearly (NEVER, ALWAYS, MUST)
- •Provide specific examples for complex behaviors
Safety and Reliability
- •Longer instructions for dangerous operations
- •Explicit anti-patterns for common mistakes
- •Clear error handling procedures
Pattern Application Discipline
DO:
- •Apply multiple patterns per section when beneficial
- •Explain why each pattern is appropriate
- •Show concrete before/after examples
- •Consider the user's specific use case
DON'T:
- •Apply patterns mechanically without rationale
- •Change text without identifying the pattern used
- •Assume patterns are obvious (always attribute)
- •Optimize for optimization's sake (preserve working patterns)
Notes
- •This process is systematic but not mechanical. Use judgment about which patterns provide value for the specific prompt.
- •When the user's prompt already uses a pattern well, acknowledge it rather than changing it.
- •Focus attribution on changes, not on what was already done well.
- •If the user requests specific optimizations (e.g., "make it more concise"), prioritize those patterns while maintaining completeness.