ai_instruction_writing

Rewrite AI instructions by transforming negative directives into clear, positive, action-oriented statements whenever the positive set is enumerable. This ensures every instruction has a primary carrier that the model can directly execute without ambiguity.

A positive-first carrier in prompt writing is an actionable directive that tells the model exactly what to do, needed when authoring or editing any AI-consumed artifact like SKILL.md files, configuration docs, or prompt templates to reduce misinterpretation.

Handle exceptions in instruction design by keeping a negative only as a necessary catch-all when it names a broader class covering a long tail of cases you cannot list positively, preserving technical precision while deleting redundant negatives.

Positive language works for system prompts and persona instruction sets by applying a self-check transformation procedure that detects inverted positives, deletes redundant negatives, and applies the right rule based on what the positive portion contains.

The best way to convert negative prompts into positive directives is to ensure the actionable positive statement comes first, applying a self-check procedure that deletes redundant negatives and applies rules based on what the positive portion contains.

You should not use positive language exclusively in prompt templates when a negative names a broader class covering a long tail of cases you cannot list positively; these necessary catch-all negatives must be preserved to maintain technical precision.