Prompt template design
Skill a5c-ai/babysitter/library/specializations/ai-agents-conversational/skills/prompt-template-design
Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration
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Structured prompt template creation with variables, formatting, and version control
SKILL.md
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Prompt Template Design Skill
Capabilities
- Create structured prompt templates with variables
- Implement prompt formatting with different styles
- Design system/user/assistant message templates
- Handle dynamic context injection
- Implement prompt versioning and management
- Create reusable prompt components
Target Processes
- prompt-engineering-workflow
- system-prompt-guardrails
Implementation Details
Template Patterns
- LangChain PromptTemplate: Variable-based templates
- ChatPromptTemplate: Message-based templates
- FewShotPromptTemplate: With example selection
- PipelinePromptTemplate: Composed templates
Configuration Options
- Variable names and defaults
- Input validation rules
- Output format specification
- Partial variable handling
- Template inheritance
Best Practices
- Clear variable naming conventions
- Structured output instructions
- Version control for templates
- Testing with edge cases
- Documentation of template purpose
Dependencies
- langchain-core