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Skill
/prompt-template-design
Structured prompt template creation with variables, formatting, and version control
Install
$ npx -y skills add a5c-ai/babysitter --skill prompt-template-design --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/prompt-template-design
Context preview
The summary Claude sees to decide when to auto-load this skill.
Structured prompt template creation with variables, formatting, and version control
SKILL.md
prompt-template-design.SKILL.mdname: prompt-template-design
description: Structured prompt template creation with variables, formatting, and version control
allowed-tools:
- Read
- Write
- Edit
- Bash
- Glob
- Grep
graph:
domains: [domain:software-engineering]
specializations: [specialization:ai-agents-conversational]
skillAreas: [skill-area:prompt-engineering, skill-area:prompt-instruction-tuning-agents]
roles: [role:ml-engineer, role:backend-engineer]
workflows: [workflow:ml-model-lifecycle, workflow:feature-development]
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
1. **LangChain PromptTemplate**: Variable-based templates 2. **ChatPromptTemplate**: Message-based templates 3. **FewShotPromptTemplate**: With example selection 4. **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
Read more
name: prompt-template-design description: Structured prompt template creation with variables, formatting, and version control allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:prompt-engineering, skill-area:prompt-instruction-tuning-agents] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:ml-model-lifecycle, workflow:feature-development]
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
1. **LangChain PromptTemplate**: Variable-based templates 2. **ChatPromptTemplate**: Message-based templates 3. **FewShotPromptTemplate**: With example selection 4. **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
Ships withbabysitter
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JavaScript
Language
MIT
License
11d ago
Last commit
8mo ago
Created
Repo: a5c-ai/babysitter
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