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prompt-engineeringlisted

Comprehensive prompt engineering framework for designing, optimizing, and iterating LLM prompts. Use when creating prompts, optimizing existing prompts, or improving AI instructions.
desilokesh1/antigravity-fullstack-hq · ★ 2 · AI & Automation · score 75
Install: claude install-skill desilokesh1/antigravity-fullstack-hq
# Prompt Engineering ## Workflow ``` User Request | +-- "Create a prompt" --> EXPLORATION PHASE +-- "Optimize this prompt" --> OPTIMIZATION PHASE +-- "Fix this issue" --> ANALYSIS PHASE ``` ## Phase 1: Exploration Before creating any prompt, understand: - What task will this prompt accomplish? - Who will use it? - What does success look like? - What are the constraints? ## Phase 2: Analysis ### Task Classification | Dimension | Options | |-----------|---------| | Complexity | Simple vs multi-step | | Output | Creative vs analytical vs structured | | Stakes | High vs experimental | ### Strategy Selection | Task Type | Approach | |-----------|----------| | Simple | Direct instructions | | Complex | Chain-of-thought | | Creative | Role setting | | Structured | Format specs + examples | ## Phase 3: Implementation ### Version 1 - Minimal - Core instructions only - Test basic functionality ### Version 2 - Enhanced - Add examples - Clarify ambiguities - Add constraints ### Version 3+ - Optimized - Refine wording - Remove redundancy ## Key Techniques ### Role Setting ``` As an experienced code reviewer, analyze... ``` ### Chain-of-Thought ``` Think step-by-step: 1. First, identify... 2. Then, analyze... 3. Finally, conclude... ``` ### Few-Shot Learning ``` Example 1: Input: "Great product" Output: { "sentiment": "positive" } Now analyze: "It was okay" ``` ### Explicit Constraints ``` - Limit to 3 paragraphs - Focus on technical aspects only - Do not include pr