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Structure a prompt so the failure mode is visible: task framing, worked examples, and asking for the reasoning you intend to check.
Passed 21 of 22 test cases with the skill, and 7 of 22 without it.
and 15 more in the full report
14 fixed7 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need to construct a prompt for an LLM to generate PostgreSQL queries from natural language requests. Most engineers just write 'Write a SQL query for X'. How should I structure this prompt so subtle schema mismatch errors or wrong join conditions are easily caught during evaluation?
| Checked | Without skill | With skill |
|---|---|---|
| The response recommends defining explicit task framing for schema constraints. | Passed | Passed |
| The response recommends including worked examples of query translations. | Missed | Passed |
| The response recommends requiring step-by-step reasoning before the generated SQL query. | Passed | Passed |
The instructions your model reads when the skill loads.
Structure a prompt so the failure mode is visible: task framing, worked examples, and asking for the reasoning you intend to check.
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.