prompt-creator

<objective>
Create highly effective prompts using proven techniques from Anthropic and OpenAI research. This skill covers all major prompting methodologies: clarity, structure, examples, reasoning, and advanced patterns.

Every prompt created should be clear, specific, and optimized for the target model.
</objective>

<quick_start>
<workflow>

1. **Clarify purpose**: What should the prompt accomplish?
2. **Identify model**: Claude, GPT, or other (techniques vary slightly)
3. **Select techniques**: Choose from core techniques based on task complexity
4. **Structure content**: Use XML tags (Claude) or markdown (GPT) for organization
5. **Add examples**: Include few-shot examples for format-sensitive outputs
6. **Define success**: Add clear success criteria
7. **Test and iterate**: Refine based on outputs
   </workflow>

<core_structure>
Every effective prompt has:

```xml
<context>
Background information the model needs
</context>

<task>
Clear, specific instruction of what to do
</task>

<requirements>
- Specific constraints
- Output format
- Edge cases to handle
</requirements>

<examples>
Input/output pairs demonstrating expected behavior
</examples>

<success_criteria>
How to know the task was completed correctly
</success_criteria>
```

</core_structure>
</quick_start>

<core_techniques>
<technique name="be_clear_and_direct">
**Priority**: Always apply first

- State exactly what you want
- Avoid ambiguous language ("try to", "maybe", "generally")
- Use "Always..." or "Never..." instead of "Should probably..."
- Provide specific output format requirements

See: [references/clarity-principles.md](references/clarity-principles.md)
</technique>

<technique name="use_xml_tags">
**When**: Claude prompts, complex structure needed

Claude was trained with XML tags. Use them for:

- Separating sections: `<context>`, `<task>`, `<output>`
- Wrapping data: `<document>`, `<schema>`, `<example>`
- Defining boundaries: Clear start/end of sections

See: [references/xml-structur