incentive-prompting

SKILL.md

Using proper prompting techniques is critical to achieving optimal AI output quality. Research shows these techniques can improve response quality by 45-115%. The difference between a mediocre AI response and an excellent one often comes down to prompt engineering. Whether you're optimizing agents, enhancing commands, or working on complex problems, applying these techniques consistently yields significantly bette...

Research-backed techniques that leverage statistical pattern-matching to elicit higher-quality AI responses. Based on peer-reviewed research from MBZUAI (Bsharat et al.), Google DeepMind (Yang et al.), and ICLR 2024 (Li et al.).

LLMs don't understand incentives, but they pattern-match on language associated with high-effort training examples. Stakes language triggers selection from distributions of higher-quality text patterns.

AI の応答品質を向上させるための研究に裏付けられたプロンプト技術 (+45 ～ 115% の改善)。プロンプトの最適化、エージェントの指示の強化、または最大の応答品質が重要な場合に使用します。 /ai-eng/optimize コマンドによって呼び出されます。専門家のペルソナ、ステーク言語、段階的な推論、課題の枠組み、自己評価テクニックが含まれます。 ソース: v1truv1us/ai-eng-system。

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