init

.opencode/skills/ai-artist/references/llm-prompting.md

@@ -0,0 +1,165 @@
+# LLM Prompting Reference
+
+## Prompt Architecture
+
+### System Prompt Structure
+```
+You are [ROLE] with expertise in [DOMAIN].
+
+## Context
+[Background, constraints, tone]
+
+## Instructions
+[Step-by-step task breakdown]
+
+## Output Format
+[Exact structure with example]
+
+## Constraints
+- [Hard limits]
+- [Guardrails]
+```
+
+### User Prompt Structure
+```xml
+<context>[Background information]</context>
+<task>[Specific action required]</task>
+<format>[Output structure]</format>
+<constraints>[Additional limits]</constraints>
+```
+
+## Reasoning Techniques
+
+### Chain of Thought (CoT)
+| Variant | Trigger | Best For |
+|---------|---------|----------|
+| Zero-shot | "Think step by step" | Quick reasoning tasks |
+| Few-shot | 2-3 reasoning examples | Complex multi-step |
+| Auto-CoT | "Let's approach systematically" | General reasoning |
+
+### Tree of Thoughts (ToT)
+```
+Explore 3 approaches to [problem]:
+For each: 1) Method 2) Pros/cons 3) Success probability
+Evaluate branches, select best path.
+```
+
+### Self-Consistency
+Run same prompt 3-5x with temp=0.7, take majority answer. Best for: math, logic, factual.
+
+### ReAct Pattern
+```
+Thought: [Current reasoning]
+Action: [Tool/step to take]
+Observation: [Result]
+...repeat...
+Final Answer: [Conclusion]
+```
+
+### Least-to-Most
+```
+Break [complex task] into subproblems.
+Solve easiest first, build up.
+```
+
+## Instruction Optimization
+
+### Self-Refine Pattern
+```
+1. Generate initial response
+2. Critique: "What's wrong with this?"
+3. Refine: "Fix identified issues"
+4. Repeat until satisfactory
+```
+
+### Role Optimization
+- **Expert persona**: "As a senior [role] with 20 years..."
+- **Constraint persona**: "You only respond with..."
+- **Teaching persona**: "Explain as if to a..."
+
+### Task Decomposition
+```
+<subtasks>
+1. [First step - output X]
+2. [Second step - using X, output Y]
+3. [Final step - using Y, output Z]
+</subtasks>
+```
+
+## Output Control
+
+### JSON Enforcement
+```
+Respond in valid JSON only:
+{"field": "type", "required": true}
+No markdown, no explanation, just JSON.
+```
+
+### Length Control
+| Goal | Phrase |
+|------|--------|
+| Brief | "In 2-3 sentences" |
+| Detailed | "Comprehensive analysis in 500 words" |
+| Structured | "5 bullet points, max 20 words each" |
+
+### Hallucination Reduction
+- "Only use information from provided context"
+- "If unsure, say 'I don't know'"
+- "Cite sources for each claim"
+- "Confidence: high/medium/low for each point"
+
+## Model-Specific Tips
+
+### Claude
+- XML tags: `<thinking>`, `<answer>`, `<context>`
+- Extended thinking: "Think deeply before responding"
+- Prefill: Start assistant response to guide format
+
+### GPT-4
+- JSON mode: `response_format: {"type": "json_object"}`
+- Function calling for structured output
+- System message for persistent instructions
+
+### Gemini
+- Multimodal: Image + text in same prompt
+- Grounding: Enable Google Search for facts
+- Safety settings: Adjust thresholds
+
+## Context Engineering
+
+### RAG Prompt Pattern
+```
+<retrieved_context>
+[Document chunks with sources]
+</retrieved_context>
+
+Answer based ONLY on context above.
+If not in context, say "Not found in documents."
+```
+
+### Window Optimization
+- Front-load critical info (primacy effect)
+- Repeat key constraints at end (recency effect)
+- Chunk long documents with summaries
+
+## Few-Shot Examples
+
+### Structure
+```
+Example 1:
+Input: [representative input]
+Output: [ideal output]
+
+Example 2:
+Input: [edge case]
+Output: [handling]
+
+Now apply to:
+Input: [actual task]
+```
+
+### Selection Criteria
+- Diverse examples > similar examples
+- Include edge cases
+- Match complexity of target task
+- 2-5 examples optimal (diminishing returns beyond)