Skills Performance Optimizer

Audit and optimize AI agent skills for token efficiency using a 40-year-old design principle.

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The Problem: Context is the Bottleneck

In an exploratory study of coding agents, researchers found that **token consumption for the same task ranged from 8,500 to over 190,000 tokens**—a 22x difference. The variable? How efficiently agents load context.

AI coding agents need to understand vast codebases comprising thousands of files and millions of lines of code. But the model's attention—its context window—is a finite and expensive resource. You cannot simply feed an entire codebase into a prompt.

**The quality of the code an agent generates is directly determined by the relevance of the code it can "see."**

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The Solution: A 40-Year-Old Design Principle

In 1981, designers at Xerox PARC faced a similar challenge: how to make powerful systems accessible without overwhelming users with complexity. Their answer was **progressive disclosure**—a principle that dictates:

*"Detail should be hidden from users until they ask or need to see it."*

Decades later, psychology proved them right. Research on algorithmic transparency found that detailed, incremental feedback was often *counterproductive*—distracting users, exposing minor errors that