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Expert prompt optimization for LLMs and AI systems.
Passed 21 of 22 test cases with the skill, and 19 of 22 without it.
2 fixed19 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
To prevent a reasoning model from outputting premature conclusions while keeping the final answer clean, inside which XML tags should the model write its intermediate reasoning steps according to Anthropic prompt patterns?
| Checked | Without skill | With skill |
|---|---|---|
| Instructs the model to write intermediate steps inside `<thinking>` or `<scratchpad>` tags | Missed | Passed |
The instructions your model reads when the skill loads.
This skill optimizes prompts for LLMs and AI systems, focusing on effective prompt patterns, few-shot learning, and optimal AI interactions.
Optimize this prompt for better results
Create a system prompt for a code review agent
Implement few-shot learning for this task
test cases passed, vs 19 / 22 without
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