think-efficiently

What problem does it solve?

Claude often wastes tokens by planning before acting and by pursuing unnecessary or redundant checks. This skill enforces an always-on efficiency framework that biases execution toward the most information-rich, smallest-step actions, reducing wasted compute and delays.

Core Features & Use Cases

• Bias toward action: applies a disciplined pre-action filter to skip needless planning and testing when a clear path exists.
• Efficiency guardrails: enforces the three Questions Before Every Action (does this produce NEW information? is this the most efficient path? is the action size proportional to the information gain?).
• Batching and parallelism: recommends parallel, small steps to reduce wall-clock time and token usage across planning, research, and deployment tasks.
• Use Case: ideal for code reviews, feature work, data analysis, and operational tasks where speed and token economy matter.

Quick Start

Before any action, apply the efficiency filter and proceed only with the most information-efficient step.