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name: engineering-prompts description: Engineers effective prompts using systematic methodology. Use when designing prompts for Claude, optimizing existing prompts, or balancing simplicity, cost, and effectiveness. Applies progressive disclosure and empirical validation to prompt development.

Engineering Prompts

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LEVEL 1: QUICKSTART ⚡

Foundation First (Always Apply):

1. Clarity: Explicit instructions + success criteria
2. Context & Motivation: Explain WHY, not just WHAT
3. Positive Framing: Say what TO do, not what NOT to do

Then Assess:

1. Simple task? → Stop here. Foundation is enough.
2. Complex task? → Add advanced techniques sparingly
3. Test & Iterate: Measure effectiveness, refine based on results

Key insight: The best prompt achieves goals with minimum necessary structure.

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LEVEL 2: DIAGNOSTICS 🔧

Output Problems → Solutions:

Process Problems → Fixes:

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LEVEL 3: THE 12 TECHNIQUES 🛠️

Foundation (Always Apply)

Note: XML is less essential with Claude 4.x - use when genuinely needed.

Advanced (Apply When Needed)

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LEVEL 4: DESIGN CHECKLIST 📋

Before Writing:

• Core task clear?
• Output format defined?
• Constraints known? (latency/cost/accuracy)
• One-off or repeated use?

Complexity Assessment:

• Simple (extraction, Q&A) → Foundation only
• Medium (analysis, code gen) → + CoT, examples
• Complex (research, novel problems) → + Chaining, role

Cost Optimization:

• Cache system prompts + reference docs (90% savings)
• Batch non-urgent work (50% savings)
• Skip CoT for simple tasks (saves 2-3x)

Deliverable:

• Prompt + techniques used + rationale + token estimate

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LEVEL 5: ADVANCED TOPICS 🚀

Tool Integration

When to use MCP tools during prompt engineering:

CopyNeed latest practices?
└─ mcp__plugin_essentials_perplexity

Complex analysis needed?
└─ mcp__plugin_essentials_sequential-thinking

Need library docs?
└─ mcp__plugin_essentials_context7

Context Management

Prompt Caching:

• Cache: System prompts, reference docs, examples
• Savings: 90% on cached content
• Write: 25% of standard cost
• Read: 10% of standard cost

Long Context Tips:

• Place documents BEFORE queries
• Use XML tags: <document>, <source>
• Ground responses in quotes
• 30% better performance with proper structure

Token Optimization

Reducing Token Usage:

• Concise, clear instructions (no fluff)
• Reuse examples across calls (cache them)
• Structured output reduces back-and-forth
• Tool use instead of long context when possible

Cost-Specific Anti-Patterns

❌ Ignoring caching - Not leveraging repeated content (90% savings lost) ❌ Over-requesting CoT - Chain of thought for simple tasks (2-3x wasted) ❌ Redundant examples - 5 examples when 2 suffice ❌ No batching - Real-time calls for non-urgent work (50% savings lost)

See LEVEL 2: Diagnostics for general fixes.

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LEVEL 6: REFERENCES 📚

Deep Dive Documentation

Detailed Technique Catalog:

• reference/technique-catalog.md - Each technique explained with examples, token costs, combination strategies

Real-World Examples:

• reference/examples.md - Before/after pairs for coding, analysis, extraction, agent tasks

Research Papers:

• reference/research.md - Latest Anthropic research, benchmarks, best practices evolution