Prompt Optimization Analyzer
A diagnostic tool designed to review and optimize skill prompts by systematically identifying token waste, anti-patterns, trigger issues, and optimization opportunities.
This skill is perfect for skill developers who want to review, debug, and prepare their skills for publication with professional-grade optimization.
Core Purpose
The Prompt Optimization Analyzer helps identify and fix common issues in skill prompts including:
- Token waste and redundancy
- Unclear trigger patterns
- Anti-patterns that reduce effectiveness
- Structural and clarity issues
- Ineffective examples
It's specifically designed for reviewing, debugging, and preparing skills for publication with actionable, specific feedback.
Six-Area Analysis Framework
1. Trigger Pattern Analysis
Evaluates whether the skill description clearly communicates when and how to use the skill. Identifies ambiguous triggers that may cause the skill to fire incorrectly or not at all.
2. Token Efficiency
Identifies redundancy, over-politeness, unnecessary elaboration, and bloated structure that waste context window tokens without adding value.
3. Anti-Pattern Detection
Flags common issues that reduce effectiveness:
- Ambiguous or vague instructions
- Conflicting instructions
- Over-specification or under-specification
- Problematic assumptions
4. Clarity and Structure
Reviews organization, logical flow, language quality, and overall readability to ensure the skill is easy to understand and follow.
5. Example Quality
Assesses whether provided examples effectively demonstrate the intended patterns and help clarify expected behavior.
6. Special Pattern Checks
Examines:
- Tool instruction clarity
- Meta-commentary effectiveness
- Conditional logic correctness
- Edge case handling
Key Features
Severity-Based Reporting
Issues are categorized by impact:
- Critical - Breaks skill functionality
- High - Significantly reduces effectiveness
- Medium - Notable improvement opportunity
- Low - Minor polish suggestions
Actionable Feedback
Every suggestion includes:
- Before/after examples showing specific changes
- Token impact estimates quantifying savings
- Concrete rewrites not just criticism
- Rationale explaining why the change helps
Common Optimization Wins
The analyzer typically identifies 20-60% token savings opportunities through:
- Removing redundant phrasing
- Consolidating repeated concepts
- Streamlining verbose instructions
- Eliminating unnecessary politeness
Red Flag Detection
Quickly identifies critical issues like:
- Skills that won't trigger properly
- Inconsistent or contradictory instructions
- Missing essential components
- Poorly scoped responsibilities
Output Structure
Analysis results are organized as:
- Overview - Quick summary of findings
- Critical Issues - Must-fix problems
- High-Priority Improvements - Significant impact changes
- Token Optimization Opportunities - Efficiency gains
- Medium/Low Priority Suggestions - Polish and refinement
- Rewrite Examples - Before/after comparisons
- Estimated Impact - Expected token savings and effectiveness gains
Framework Principles
The analyzer emphasizes:
- Specificity - Concrete, actionable feedback
- Impact Visibility - Clear token savings estimates
- Solution-Oriented - Provides rewrites, not just critique
- Intent Respect - Preserves the skill author's original goals
Repository Resources
Visit the Prompt Optimization Analyzer repository for complete documentation and the full analysis framework.
About This Skill
This skill was created by Nate Jones as part of his comprehensive Nate's Substack Skills collection. Learn more about Nate's work at Nate's Newsletter.
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Diagnostic tool for reviewing and optimizing skill prompts by identifying token waste, anti-patterns, trigger issues, and optimization opportunities.