Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →sickn33/prompt-engineering
Expert guide on prompt engineering patterns, best practices, and optimization techniques.
Passed 22 of 22 test cases with the skill, and 20 of 22 without it.
2 fixed20 passed either way0 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.
We are designing a prompt layout sequence for a document parsing pipeline. Is it better to put the variable document text before the task instructions and output format specification, or what is the recommended structural hierarchy order?
| Checked | Without skill | With skill |
|---|---|---|
| Places system context and task instructions before input data and output format | Missed | Passed |
The instructions your model reads when the skill loads.
Advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
Teach the model by showing examples instead of explaining rules. Include 2-5 input-output pairs that demonstrate the desired behavior. Use when you need consistent formatting, specific reasoning patterns, or handling of edge cases. More examples improve accuracy but consume tokens—balance based on task complexity.
Example:
Extract key information from support tickets:
Input: "My login doesn't work and I keep getting error 403"
Output: {"issue": "authentication", "error_code": "403", "priority": "high"}
Input: "Feature request: add dark mode to settings"
Output: {"issue": "feature_request", "error_code": null, "priority": "low"}
Now process: "Can't upload files larger than 10MB, getting timeout"
Request step-by-step reasoning before the final answer. Add "Let's think step by step" (zero-shot) or include example reasoning traces (few-shot). Use for complex problems requiring multi-step logic, mathematical reasoning, or when you need to verify the model's thought process. Improves accuracy on analytical tasks by 30-50%.
Example:
Analyze this bug report and determine root cause.
Think step by step:
1. What is the expected behavior?
2. What is the actual behavior?
3. What changed recently that could cause this?
4. What components are involved?
5. What is the most likely root cause?
test cases passed, vs 20 / 22 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.